About the Synthetic Chemistry, CMC and Logistics team

Our dynamic team of Synthetic Chemists and CRO Leads are dedicated to transforming drug design and manufacturing. We work in partnership with our AI/ML and drug discovery colleagues to support all phases of chemistry, from early to late stages, as well as managing our extensive external CRO team. We promote a supportive atmosphere where the diverse expertise of every team member is recognised and appreciated. We maintain a strong growth mindset, with continuous development and learning as a priority.

If you are a skilled and ambitious scientist looking to take the next step in your career, joining Isomorphic Labs will lift you out of your comfort zone and provide you with an amazing opportunity for personal growth and development.

Your impact

As part of the ongoing expansion of our Drug Design and Medical Research function, we are hiring Synthetic Chemists who are keen to impact medicinal chemistry projects and/or CMC projects. You will support the business alongside world-leading AI/ML Drug Design Platform teams. You will deliver scientific expertise and strategic direction to drive improvements in the Platform and the advancement of active drug discovery programs.

What you will do 

• Apply your Synthetic Chemistry expertise across Medicinal Chemistry and/or CMC projects.
• Act as a Synthetic Chemistry Lead in one or more active drug discovery programs.
• Collaborate both internally and with third party organisations, interacting within multidisciplinary teams to support the data-driven delivery of high quality scientific solutions to complex technical problems.
• Work cross-functionally with the Medicinal Chemistry, DMPK, Biology, and Technology teams.
• Represent the company externally, interacting with existing and prospective collaborators including Contract Research Organisations (CROs) and Contract Development & Manufacturing Organisations (CDMOs).
• Prepare detailed scientific proposals and reports to support new and ongoing programs.
• Embrace and champion our culture of inclusion and continuous professional development.

Skills and qualifications 

Essential:

• PhD in Synthetic Chemistry, or a related technical field, or equivalent industrial experience.
• 3+ years’ professional experience in a Chemistry role, operating within a biotech, pharma or CRO setting. 5+ years' experience for more senior positions.
• Solid technical foundation in synthetic chemistry with previous experience operating independently as an individual contributor.
• Excellent problem-solving and decision-making capabilities applied to complex synthetic chemistry challenges.
• Experience of working with and closely managing CRO and/or CDMO resources.
• A genuine passion for drug discovery and enthusiasm for the potential of AI/ML to transform the field.
• Excellent communication (written and verbal) and interpersonal skills, with an ability to work effectively in a cross-functional, collaborative team environment.
• Track record of creative problem solving with a strong growth mindset, adaptability, and eagerness to learn new concepts and techniques.

Your impact 

As the PKPD Lead, you will develop the quantitative pharmacology strategy of drug discovery projects to deliver high quality clinical candidates, whilst using and contributing to the optimisation of state-of-the-art computational and AI drug design models. As part of the DMPK and Quantitative Pharmacology team, you will champion the use of model-informed drug discovery and development on both small molecule and biologics projects. You will work closely with the Biologics Discovery team to further develop AI models for biologics developability.

If you are an experienced and ambitious scientist looking to play an active part in the AI-driven transformation of the pharmaceutical industry, joining Isomorphic Labs will lift you out of your comfort zone and provide an amazing opportunity for personal growth and development.

What you will do 

PKPD Lead

• Design and implement quantitative pharmacology strategies with an AI-first approach, from target identification to pre-clinical development.
• Provide scientific leadership and integrate PK and quantitative pharmacology strategies for biologics projects, within the broader project strategy. As a member of the project core team, you will collaborate closely with colleagues in Drug Design, Pharmacology, ML Engineering, and Preclinical and Clinical Development to resolve PK and PD challenges.
• Develop advanced PKPD models for biologics and small molecule projects in collaboration with the DMPK and Pharmacology Leads.
• Contribute to the choice of modality that is the most appropriate for each target. Develop the target molecule profile at the inception of the project.
• Integrate PK, PD and toxicological data to extract decision-making information through mechanistic and empirical models, including dose and safety margin predictions for biologics projects.
• Author PKPD sections of regulatory documents.

ML interactions

• Partner with Machine Learning colleagues to integrate PK and PD aspects of the drug design platform and identify, generate and analyse data from which to develop and improve predictive models.
• Identify state-of-the-art integration methods that could bring transformational benefits to our platform or ways of working.
• Support the development of the biologics developability platform by identifying high-throughput techniques to predict the PK behaviour of various biologics formats.

CRO interactions

• Since IsomorphicLabs outsource all wet-lab work to external vendors, you will maintain and develop close relationships with the CRO network to:
• Ensure high quality and timely data generation to support our portfolio projects.
• Leverage the scientific expertise of our external collaborators to enhance the team's impact.
• Oversee the delivery of data generation campaigns purposefully designed to support the development of AI-based developability models.

People

• Mentor junior members of the DMPK and Quantitative Pharmacology  team.
• Embrace and champion a culture of inclusion and continuous professional development.

Skills and qualifications 

Essential:

• PhD in either Pharmaceutical Science, Pharmacy, or Chemistry or another relevant subject.
• 3+ years of related experience in the pharmaceutical industry.
• Experience as a PKPD Lead, solving PKPD-related problems in biologics projects with a track record of working collaboratively to deliver high quality candidates.
• Practical experience developing high quality quantitative pharmacology packages to support early clinical development, including authoring and reviewing regulatory documents, ideally in oncology.
• Advanced knowledge of PK and PKPD modelling for biologics.

Nice to have:

• Good understanding of machine learning techniques.
• Familiarity with Python and KNIME.

About the DMPK and Quantitative Pharmacology team

The DMPK and Quantitative Pharmacology team, part of the Preclinical Development group, accelerates the delivery of high quality drug candidates by developing innovative and creative AI-first solutions. By applying our domain expertise and through collaboration with the entirety of our world-class drug discovery disciplines and ML researchers, we ensure that drug-like properties are at the heart of our drug design engine. We shape the development of state-of-the-art ADME and toxicology predictive models. We rethink drug discovery from Hit ID to first-in-human (FIH) trials by optimising the context of use of these models.

Your impact

At Isomorphic Labs, DMPK Leads drive the DMPK strategy of drug discovery and development projects to deliver high quality clinical candidates whilst using and contributing to the optimisation of state-of-the-art computational and AI ADME models. 

As part of the Drug Design and Medical Research team and through close collaboration with the Technology teams, you will support the business alongside world leading AI/ML Drug Design Platform teams. You will collaborate to deliver scientific expertise and strategic direction to drive both improvements in the Platform and apply this to real drug design projects. You use your expertise in PBPK modelling to make data integration a powerful tool to accelerate drug design and preclinical development.

If you are a skilled and ambitious scientist looking to take the next step in your career, joining the Isomorphic Labs now will lift you out of your comfort zone and provide you with an amazing opportunity for personal growth and development.

What you will do 

• Define Iso’s PBPK strategy leading to fit for purpose models that drive drug design and accelerate accelerate preclinical development.
• Design and implement stage-appropriate development DMPK strategies with AI-first approach, integrate the quantitative pharmacology and overall project strategies.
• Design mechanistic experiments to support project progression in a data-driven manner.
• Integrate DMPK, PD and toxicological data to extract decision-making information, including dose and safety window predictions.
• Define Quantitative Pharmacology strategy in collaboration with Pharmacology Leads.
• Optimise molecule design and formulation based on physico-chemistry and biotransformation knowledge in collaboration with Chemistry Leads.
• Maintain knowledge of state-of-the-art technologies and methods to increase confidence in human PK prediction.
• Author DMPK sections of regulatory documents.
• Embrace and champion a culture of inclusion and continuous professional development.
• Optimise the use of Iso’s datasets to address fundamental DMPK questions and advance the field.

Skills and qualifications 

Essential:

• PhD in either Pharmaceutical Science, Pharmacy, Chemistry, or another relevant subject.
• 5+ years’ professional as a DMPK Lead, solving DMPK-related problems in preclinical development with a track record of working collaboratively to deliver regulatory-ready FIH packages.
• Practical experience in setting up automated PBPK workflows.
• Practical experience in using PBPK to support preclinical development.
• Practical experience developing DMPK and quantitative pharmacology packages to support early clinical development, including authoring and reviewing regulatory documents, ideally in oncology.
• Advanced knowledge of PK and PKPD modelling.
• Experience of partnering closely with Preclinical and Clinical teams.

Nice to have:

• Experience with biologics, peptides and other new modalities.
• Good understanding of machine learning techniques.
• Familiarity with Python and KNIME.

About the DMPK and Quantitative Pharmacology team

The DMPK and Quantitative Pharmacology team, part of the Preclinical Development group, accelerates the delivery of high quality drug candidates by developing innovative and creative AI-first solutions. By applying our domain expertise and through collaboration with the entirety of our world-class drug discovery disciplines and ML researchers, we ensure that drug-like properties are at the heart of our drug design engine. We shape the development of state-of-the-art ADME and toxicology predictive models. We rethink drug discovery from Hit ID to first-in-human (FIH) trials by optimising the context of use of these models.

Your impact

At Isomorphic Labs, DMPK Leads drive the DMPK strategy of drug discovery projects to deliver high quality clinical candidates whilst using and contributing to the optimisation of state-of-the-art computational and AI ADME models. 

As part of the Drug Design and Medical Research team and through close collaboration with the Technology teams, you will be supporting the business alongside world leading AI/ML Drug Design Platform teams. You will collaborate to deliver scientific expertise and strategic direction to drive both improvements in the Platform and apply this to real drug design projects. 

If you are a skilled and ambitious scientist looking to take the next step in your career, joining Isomorphic Labs will lift you out of your comfort zone and provide you with an amazing opportunity for personal growth and development.

What you will do 

• Design and implement stage-appropriate DMPK strategies with AI-first approach, integrating quantitative pharmacology and overall project strategies.
• Design screening cascade and mechanistic experiments to support project progression in a data-driven manner.
• Integrate DMPK, PD and toxicological data to extract decision-making information, including dose and safety window predictions.
• Define Quantitative Pharmacology strategy in collaboration with Pharmacology Leads.
• Optimise the use of Iso’s datasets to address fundamental DMPK questions and advance the field.
• Optimise molecule design based on physico-chemistry and biotransformation knowledge in collaboration with Chemistry Leads.
• Maintain knowledge of state-of-the-art technologies and methods to increase confidence in human PK prediction.
• Author DMPK sections of regulatory documents.
• Embrace and champion a culture of inclusion and continuous professional development.

Skills and qualifications 

Essential:

• PhD in either Pharmaceutical Science, Pharmacy, Chemistry, or another relevant subject.
• 3+ years’ professional experience as a DMPK Lead, solving DMPK-related problems in drug discovery with a track record of working collaboratively to deliver high quality candidates.
• Practical experience developing DMPK and quantitative pharmacology packages to support early clinical development, including authoring and reviewing regulatory documents, ideally in oncology or immunology.
• Experience of partnering closely with Preclinical and Clinical teams.
• In depth knowledge of biotransformation.
• In depth knowledge of PK modelling and scaling of ADME properties.

Nice to have:

• Experience with biologics, peptides and other new modalities.
• Advanced knowledge of PKPD modelling.
• Good understanding of machine learning techniques.
• Familiarity with Python and KNIME.

Your impact

As InfoSec Technical Program Manager, you will translate Isolabs’ security strategy into engineering reality. Reporting to the CISO, with a strong functional tie to the TPM Discipline Lead, you will operate at the critical intersection of risk management and research velocity. You will steer the InfoSec Roadmap, driving complex security initiatives—from protecting proprietary AI models to embedding Zero Trust architecture—across a fast-moving, highly regulated landscape. 

Going beyond traditional project management, you are a technical enabler who partners directly with engineering and ML teams. You will navigate architectural roadblocks, secure sensitive drug discovery pipelines, and ensure leadership has the data-driven, operational visibility needed to protect a pioneer in digital biology.

What you will do

• Structure and drive multi-quarter security project roadmap, balancing long-term strategic initiatives (e.g., Cloud Security, Platform IAM, Secure SDLC) with immediate business needs.
• Lead ad-hoc initiatives and high-priority business requests, such as securing sensitive regulated data transfers for drug discovery to architecting guardrails for novel Agentic AI workflows.
• Drive the end-to-end delivery of security projects by working hand-in-hand with engineers, navigating the complex Alphabet/Google Ecosystem, and ensuring high-quality execution.
• Educate and advocate for InfoSec across the business, acting as a “product manager” regarding InfoSec’s capabilities, assets, responsibilities, and SLAs.
• Build extensive and trusting relationships with engineers, researchers and leaders across the company. Act as the bridge between the business and security in order to provide balanced recommendations to the CISO and the TPM Lead.
• Design automated, data-driven dashboards that provide the CISO and engineering leaders with clear visibility into program health, operational KPIs, and risk reduction metrics.

Skills and qualifications 

Essential:

• Technical Credibility: Deep fluency across Security, Tech, and AI, allowing you to partner effectively with senior engineers and researchers.
• Strategic Execution: Proven track record of driving complex roadmaps from concept to delivery. You excel at navigating ambiguity and taking decisive action when scientific and financial stakes are high.
• Pragmatic Risk Management: Ability to make calculated trade-offs between security posture, technical debt, and research velocity without stalling innovation.
• Cross-Functional Influence: Exceptional ability to influence without formal authority, championing security as a core priority across engineering, ML, and business teams.
• Proactive Problem Solving: You anticipate architectural bottlenecks, untangle cross-team dependencies, and turn complex organisational friction into clear, actionable project plans.
• Translational Communication: Highly skilled at translating CISO’s objectives into technical requirements and condensing complex technical and organisational challenges into concise and actionable plans for leadership.

Nice to have:

• Domain expertise in highly regulated, data-intensive industries (Life Sciences, Pharma, Deep Tech).
• Hands-on experience navigating GCP and the internal Alphabet/Google ecosystem (on-corp)
• Engineering background with hands-on skill regarding Cloud Architecture, Zero Trust, IAM, and security observability.
• Familiarity with  InfoSec and AI Management Frameworks (ISO 27001, ISO 42001) and emerging AI security frameworks (e.g., OWASP Top 10 for LLMs, MITRE ATLAS).
• Industry-standard security or program management certifications (e.g., CISSP, CISM, CCSP, or Agile/Scrum methodologies).

Your impact

As a Senior InfoSec Specialist, you will be a cornerstone of our Governance Risk and Compliance (GRC) function, with a primary focus on securing our supply chain and third-party ecosystem. Reporting to the InfoSec Risk and Governance Lead, you will ensure that our innovative partnerships - from SaaS providers to Clinical Research Organisations (CROs) - meet our security standards. You will also play a key role in enhancing our ISMS and supporting secure business operations, including our drug discovery and clinical activities. Your work directly protects our organisation and ensures the right balance between business objectives and security is sustained.

What you will do

• Coordinate the third party security risk management lifecycle: execute the end-to-end third-party risk process, including initial intake, technical due diligence, risk-based tiering, ongoing monitoring, secure offboarding, and liaising with Legal and Finance teams.
• Perform detailed vendor assurance activities commensurate with their risk profile, ensuring alignment with legal, regulatory, contractual and policy requirements.
• Continuously develop and refine assessment methodologies to evaluate and audit vendors.
• Promote operational efficiency by building and maintaining third party security risk management dashboards and automating evidence collection to provide real-time visibility into the vendor risk landscape.
• Provide expert guidance to medicinal and ML research colleagues on complex risk topics, translating technical issues into clear business impact statements
• Support the InfoSec Risk and Governance Lead in improving and maintaining the Isomorphic Labs ISMS and other regulated and contractual data assurance requirements, including internal audit execution and control testing.
• Develop a unified GRC framework able to provide internal and external assurance for all relevant legal, regulatory, contractual and policy requirements.
• Coordinate, author and maintain security policies and processes, ensuring they reflect reality as well as meeting our legal, regulatory, and contractual requirements.
• Support the development of secure, lean pharma and clinical operations with an AI-first approach.

Skills and qualifications 

Essential:

• Capacity to prioritise critical inquiry over rote compliance - you must be able to critically think through risks and issues and provide timely, accurate and enabling advice suitable to the business.
• Ability to excel as an individual contributor with the agility and adaptability to quickly pivot between strategic to operational levels, and between widely differing contexts.
• Strong understanding of risk management with a proven ability to manage the full risk management lifecycle, from technical risk identification and analysis to presenting clear, business-focused mitigation options.
• Robust knowledge of information technology and cybersecurity, including cloud and ML-based environments.
• Experience leading internal and external assurance activities.
• Knowledge of relevant security and compliance standards (e.g. ISO 27001, NIST).
• Experience managing the security threats posed by a complex third-party ecosystem, including cloud providers.
• Demonstrated experience in life sciences, technology, or AI industries.
• Open-minded and innovative approach in meeting regulatory requirements, balancing compliance with the efficiency demands of ML-driven drug discovery.
• A natural ability to build credibility and influence decision-making across scientific, engineering, corporate and leadership functions to drive the security agenda forward.

Nice to have:

• A deep experience of the Pharma Industry and Drug Development process and ecosystem is a plus
• Experience in threat modelling.
• Interest in / experience of GRC engineering.
• Interest in / experience of Cyber Risk Quantification.
• Familiarity with AI-specific threats and security controls, such as those addressing model inversion, data poisoning, or adversarial attacks.
• Relevant certifications (e.g. CISA, CISSP).
• Experience automating evidence collection and control monitoring.
• Contribution to open-source security projects or participation in security communities.

Senior Engineering Manager, London 

Your impact 

Reporting directly to the Head of Engineering, you will be responsible for the strategic direction, execution, and operational excellence of our Platform teams, which are enabling training and serving of the largest foundations models in biotech. These teams include Technical Infrastructure, Machine Learning Platform, Site Reliability team and Developer Experience for Research. This is a highly influential role that requires a blend of deep technical expertise, strong leadership capabilities, and a passion for fostering a high-performance engineering culture. Your work has the potential to accelerate cutting edge research in the drug design space.

What you will do

• Define and execute the long-term vision and strategy for our foundational infrastructure, aligning with company goals and anticipating future needs.

• Lead, mentor, and inspire a diverse team of engineering managers and individual contributors across multiple disciplines (ML Platform, Tech Infrastructure, SRE). Foster a culture of innovation, collaboration, continuous learning, and accountability.

• Oversee the development and evolution of our core platform, ensuring it provides robust, scalable, and developer-friendly services for all engineering teams. This includes aspects like service mesh, container orchestration, CI/CD pipelines, and internal tooling.

• Lead the teams responsible for building and maintaining the underlying systems that power our user-facing applications, focusing on performance, reliability, and seamless user experiences.

• Guide the development and operation of the infrastructure supporting our prediction models, ensuring high availability, low latency, and efficient data processing for machine learning initiatives.

• Drive the strategy and execution for our core technical infrastructure, including networking, compute, storage, and data centers (on-prem and/or cloud). Optimize for cost, performance, and security.

• Champion and embed SRE principles across the organization. Oversee the SRE team responsible for ensuring the reliability, scalability, and performance of our critical systems through proactive monitoring, incident management, and automation.

• Establish and enforce best practices for infrastructure operations, including monitoring, alerting, capacity planning, disaster recovery, and security. Drive continuous improvement in system stability and uptime.

• Partner closely with product engineering teams, security, data science, and other stakeholders to understand their needs and deliver foundational solutions that accelerate product development and innovation.

• Evaluate and manage relationships with key internal partners to ensure optimal value and performance.

• Manage the budget for the Foundations Engineering organization, optimizing resource allocation and identifying cost-saving opportunities.

Skills and qualifications 

Essential:

• Experience in software engineering, with a significant portion focused on ML infrastructure, platform, or site reliability engineering.
• Demonstrated experience in a leadership role, managing multiple engineering teams and managers.
• Deep understanding of distributed systems, cloud architectures (AWS, Azure, GCP), and modern infrastructure technologies.
• Proven experience with running horizontal Platform Engineering teams
• Strong background in Site Reliability Engineering (SRE) principles and practices, including incident management, observability, performance optimization, and automation.
• Familiarity with data infrastructure and systems supporting machine learning/prediction models.
• Excellent communication, interpersonal, and presentation skills, with the ability to articulate complex technical concepts to both technical and non-technical audiences.
• Demonstrated ability to attract, hire, retain, and develop top engineering talent.
• Strategic thinker with a proven ability to define and execute complex technical roadmaps.
• Strong problem-solving skills and a data-driven approach to decision-making.
• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.

Nice to have: 

• Experience in a high-growth, fast-paced environment.
• Experience building and scaling infrastructure for Biotech, Life science ADD

About the Exploratory Sciences Team

Join our expanding Exploratory Sciences team, focused on tackling proteins which are critical for disease biology, but have been traditionally considered intractable. We are a small, multidisciplinary team within the Drug Design and Medical Research function at Isomorphic Labs. We work at the interface of machine learning, chemical biology and drug discovery to apply our platform to some of the toughest problems in drug discovery, and we collaborate closely with multiple teams across Isomorphic Labs. We have a strong growth mindset and prioritise continued development and learning as we hope to build the next generation of drug discovery scientists.

We are expanding and investing in our multidisciplinary Induced Proximity team within Exploratory Sciences, looking to recruit a number of talented scientists to drive projects towards the clinic. This role is for a Chemistry Lead, specialising in induced proximity. We're also willing to consider applications from those with PhD experience in molecular glue design and synthesis but no professional experience yet, as we plan to open junior positions within this team in the near future.

Your impact

As a member of the Induced Proximity team, you will deliver the development and application of a state-of-the-art induced proximity design platform. This will involve applying our platform in novel ways, and critically driving portfolio projects towards the clinic. You will need to design and execute on bold strategies to tackle problems that are currently considered impossible. Working alongside world leading AI/ML and Drug Design Platform teams. You will collaborate to deliver scientific expertise and strategic direction to drive both improvements in the Platform and apply this to unsolved drug design problems.

Ready to elevate your scientific career? Isomorphic Labs offers ambitious scientists a unique environment to tackle stimulating challenges, pushing your boundaries and accelerating your personal and professional growth. If you are a skilled and ambitious scientist looking to take the next step in your career, joining the Isomorphic Labs will challenge you with novel problems and provide an unparalleled opportunity for professional growth and development.

What you will do 

• Apply your knowledge of cutting-edge molecular glue design and synthesis to tackle long standing challenges in drug discovery.
• Utilise internal AI/ML models to solve challenging drug discovery problems.
• Collaborate both internally and with third party organisations, interacting within multidisciplinary teams to support data-driven delivery of high quality scientific solutions. This will require understanding the fundamentals of diverse disciplines including ML, Biology, Chemistry and DMPK, and communicating effectively with experts in those fields. 
• Represent the company externally, interacting with existing and prospective collaborators and contract research organisations (CROs).
• Prepare detailed scientific proposals and reports to support new and ongoing programs.
• Embrace and champion our culture of inclusion and continuous professional development.

Skills and qualifications 

Essential:

• PhD in Chemistry, or a related technical field, or equivalent experience.
• 3+ years’ professional experience in a Chemistry role, either operating within a biotech or pharma setting, or within a Post Doc position.
• Practical experience in the design and synthesis of chemical inducers of proximity/molecular glues, ideally with experience of applying these skills to active drug discovery projects.
• Broad knowledge of current chemical biology techniques.
• Experience of coding in Python, or a willingness to learn in-role.
• A genuine passion and enthusiasm for applying AI/ML to drug design and how this can transform the field.
• Excellent communication (written and verbal) and interpersonal skills, with an ability to work effectively in a cross-functional, collaborative team environment.
• A track record of creative problem solving with a strong growth mindset, adaptability, and eagerness to learn new concepts and techniques.

Nice to have:

• Experience working with or managing activities at contract research organisations (CROs).
• Experience of contributing to structure-based drug design (SBDD) problems.
• Experience of applying ML methods to Drug Discovery problems.
• Track record of authorship of relevant scientific manuscripts.

Your Impact

We are seeking a Senior Translational Oncologist to serve as a key scientific leader to develop and execute the complete translational strategy for our diverse oncology pipeline, spanning multiple therapeutic modalities. You will work in a deeply collaborative, interdisciplinary partnership with our Computational Biology, AI/ML, Drug Design and Clinical teams. In this vital role, you will also be expected to line manage a team of Biologists, driving projects from discovery through to early clinical development.

Your primary objective is to define the path to the clinic, and build the biomarker and patient selection strategies that ensure we get the right drug to the right patient, providing robust evidence that the target molecular profiles of AI-designed oncology drugs translate into desirable target product profiles.

What you will do

• Translational Strategy: Design, lead, and execute comprehensive translational strategies for our oncology portfolio, establishing a clear line-of-sight from preclinical validation to clinical efficacy.
• Oncology Model Implementation: Ensure Isomorphic labs is choosing and accessing the most appropriate state-of-the-art in vivo and ex vivo cancer models (e.g. PDX, tumour organoids, syngeneic models, and complex co-cultures) to rigorously test mechanism of efficacy, resistance mechanisms, patient stratification, and dosing regimens.
• Biomarker & PoC: Develop and implement robust biomarker and pharmacodynamic (PD) strategies, informed by in silico predictions, to secure early clinical proof-of-concept and guide patient selection in conjunction with Translational Medicine.
• AI/ML Partnership: Serve as the key oncology expert in a "computational-experimental" feedback loop. You will collaborate with Computational Biologists and ML Engineers to interpret in silico findings, design critical validation experiments, and integrate high-dimensional experimental data back into the AI platform to refine our models.
• Team Leadership & Development: Lead a small team of drug discovery scientists who are responsible for the biology strategy in oncology drug discovery projects. Provide scientific leadership and mentorship, fostering a culture of high performance, innovation, and rigorous scientific inquiry.
• Regulatory Contribution: Author and provide expert contribution to the translational and biomarker sections of key internal documents and external regulatory filings (e.g. INDs).
  
  
  

Skills and qualifications 

Essential:

• PhD in Oncology or Cancer Biology, or a related scientific discipline, or equivalent industrial experience.
• 10+ years’ professional experience in a pharmaceutical or biotech setting.
• Proven track record in translational science, pharmacology, and biomarker development within oncology.
• Deep, expert-level understanding of cancer biology, including oncogenic signaling pathways, the tumor microenvironment (TME), and mechanisms of drug resistance.
• Demonstrable success in building comprehensive translational packages (e.g. PK/PD, efficacy, and biomarker strategies) that have guided programs from discovery into early clinical development.
• Expert knowledge in developing and utilising innovative translational models (e.g. human ex vivo assays, complex in vivo models) to probe disease biology and drug response.
• Proven experience in a leadership role, specifically managing direct reports and leading biology or translational sub-teams from program inception to clinical candidate delivery.
• Strong understanding of the competitive landscape in oncology and current standards of care.
• Exceptional communication skills, with a proven ability to "speak the language" of both computational scientists and discovery biologists, fostering true interdisciplinary collaboration.

Nice to have

• Understanding of (and enthusiasm for) how AI/ML models are used in drug discovery.
• Experience with diverse therapeutic modalities, including small molecules, biologics (ADCs, bispecifics), or novel modalities.
• Proven drug discovery project leadership from target selection through to candidate nomination.

We are currently accepting expressions of interest from experienced: 

• Software Engineers
• ML Research Scientists
• ML Research Engineers 
• ML Engineers
• Computational Chemists
• Technical Project/Program Managers
• Or general applications.

Please note:

If you have previously registered your details we will be in touch if/when something suitable opens up - you do not need to reapply.

We are receiving huge levels of interest so our response may not be immediate, however, if a relevant role opens up, we'll be sure to reach out and connect. 

Thank you for your interest in Iso Labs!  

As an Operating Partner you'll be part of a small but high bandwidth, highly productive team specialising in catalysing business critical initiatives across Iso through partnership with cross-functional organisational leaders. Together we crystallise the ‘what’ and ‘why’ to unlock the ‘how’ with clarity and at pace, with a commitment to operational excellence and what's right for the organisation, facilitating maximum productivity and progress towards our mission. Agility, organisation and nimbleness are critical and this role will evolve alongside the leadership team’s role and needs as we advance towards our mission.

What you will do 

• You’ll work shoulder-to-shoulder with the Chief Scientific Officer and Chief Research Officer (Drug Design) and their teams to deliver and operationalise the highest-priority initiatives in their org areas, in particular where cross-organisational influence and expertise is needed.
• Drive impact: You’ll enable leaders and their teams to scale effectively by advising and soundboarding on their ideas for how to maximise their impact, focus on the things only they can do and empower and enable those around them; you’ll do this by synthesising outputs, problem solving across functions and driving solutions forward. 
• Deliver: While no task is too big or too small, you’ll focus your time and energy on maximising impact and output alongside the Chief Scientific Officer and Chief Research Officer (Drug Design) for the benefit of the organisation. You’ll be a doer as well as a thought partner: you’ll follow up, close loops in a timely fashion and drive initiatives to completion in alignment with leadership and organisational needs. You’ll have a keen sense of when to bring things back (e.g. paused/’not yet’ initiatives), achieve alignment and develop a plan to make it happen. 
• Collaborate: You’ll identify what is important/needs to be done by leadership and what can be done by others to support, ensuring clear roles and responsibilities are in place. You’ll build relationships with key stakeholders across Iso to gain a holistic understanding of the organisation, instilling high levels of trust and providing hands-on partnership, counsel and input on important projects, initiatives and decisions. 
• Big picture view: You’ll anticipate and propose solutions to issues and risks and share critical information with key stakeholders and prepare, present and gain agreement on proposals among leadership and then lead and influence teams to execute - leveraging strong leadership, communication and influencing skills and problem solving with creativity and innovation.
• Drive efficiency: You’ll empower others to be maximally efficient by optimising for leanness and proactively spotting and breaking down blockers and inefficiencies, balancing what the organisation needs in the short and longer term with a keen eye for how to scale most efficiently and effectively.
• Prioritise: You’ll assess what’s most important vs doing everything by clearly disambiguating what’s ok to be ‘good enough’ from what will turbo-charge the organisation; you’ll do this in partnership with leads and other partner roles e.g. StratOps partners, EAs, TPMs and product by connecting people, ideas and thinking to proactively drive a joined-up approach.

Skills and qualifications

Essential:

• Drug design domain expertise, for example an educational background in Chemistry or Biology and experience working in biotech and/or pharma.
• Experience partnering with leaders in fast-paced and constantly changing environments, acting as a sounding board on important projects, initiatives and decisions and as individuals go through the change cycle.
• You’re confident engaging with technical topics and initiatives even when you don’t have a deep understanding, and you have the ability to probe, synthesise information and move conversations forward.
• You are comfortable with ambiguity and enjoy environments where you can implement creative and innovative ideas and solutions which drive organisational performance. You can adapt to the needs of the organisation and are highly resilient.
• You enjoy variety and have a ‘get stuck in’ mentality - no task is too big or too small.
• You are experienced in breaking complexity down to make tangible, positive progress across the organisation by prioritising, planning and executing with clarity and pace.
• You are able to act and communicate with confidence in a high performance culture, instilling trust in everyone you interact with, delivering well thought through solutions. You can turn your hand to most things and if you don’t know the answer you are tenacious in finding out.
• You demonstrate a curious attitude and role model commitment to learning and understanding more about work across the whole organisation to enhance the impact of you and others.
• You’re highly organised, resourceful and have proven experience managing your own work and projects.
• You enjoy operating independently but love being part of a highly supportive and collaborative team. You share information and understand that succeed or fail, we do so as a team.
• You are looking for a career defining role and are ready to commit to this long term mission. The chance to be a key part of something extraordinary; the opportunity to make a real difference.

Nice to have:

• Experience in a Chief of Staff or similar role. 
• Knowledge and experience in utilising coaching techniques to support individuals from diverse backgrounds in a dynamic environment.
• Experience in performing a similar role in a start-up or other high growth organisation.
• Knowledge of AI and/or Tech.

Software Engineer (Fleet Management), London 

Your impact 

We are building the largest foundation models in biotech and applying them immediately to cure disease. You will play a key role and work at a grand scale to deliver the foundations that make this happen. By partnering with in-house machine learning experts and biotech researchers you will join a team to efficiently scale and plan the base on which our groundbreaking AI is built.

What you will do 

• You will focus on the end-to-end GPU/TPU (accelerator) strategy, designing infrastructure, optimizing performance, and integrating new hardware to leverage advancements. In partnership with our Machine Learning Platform team, regularly work in the environment to push and support deployments. Regularly be building, monitoring and managing cluster deployments.
• Support the technical strategy around hardware acquisition and deployment decisions
• Drive research and efficiency design around the infrastructure up to the point of service to the ML platforms teams
• Contribute to the efforts for consistently improving the reliability of our ML runs
• Operate and handle research, development, and production cloud infrastructure and systems
• Partner and collaborate with a diverse set of teams incl. science, research, product, business development and operations
• Contribute to core technical decisions (e.g. choice of tooling, infrastructure, and architectural design)

Skills and qualifications 

Essential:

• Possess real world experience of large scale AI/ML workloads
• Have experience working in cloud compute infrastructure design, preferably GCP
• Possess strong programmings skills
• Have significant experience working and deploying in Kubernetes
• Familiarity with the Nvidia GPU generations

Nice to have:

• Have a background in either ML SWE or infrastructure SRE work to build on
• Have experience leading and delivering projects to multidisciplinary stakeholders
• Familiarity with Google TPU generations
• Familiarity with: workload scheduling; machine learning efficiency research; familiarity with ML-driven R&D cycles; familiarity with hardware benchmarking

About the Translational Sciences Team

We are building a dynamic drug discovery team in Boston, as part of Isomorphic Labs’ approach to transform how drugs are designed. Translational Sciences is an essential component of this effort, establishing and evolving our biological understanding of how to correct dysregulated systems in disease. This team will have impact across the full breadth of our portfolio, from critical input on target selection to essential partnership on biomarker development, to enable pharmacodynamic modulation and target engagement in the clinic.  Domain expertise will be critical to design translational strategies for programs, evolving our understanding of mechanisms and modes of action as programs progress.  This team will be highly collaborative and need to establish strong scientific relationships with multiple groups in the company, from Medicinal Chemists to Applied Machine Learning Scientists, creating a powerful symbiotic relationship that drives our internal and collaborative portfolios.

What you will do 

• Lead the preclinical Translational Science strategy in close collaboration with the Computational Biology, Preclinical Development and Translational Medicine teams, ensuring lifecycle-spanning screening cascades and biomarker assays are in place to guide programs toward clinical success.
• Ensure scientific rigor and "decision-quality" data across all local programs.
• Partner with the VP, Head of Drug Discovery, Cambridge, MA to recruit and retain a world-class team of scientists.
• Maintain a seamless collaborative loop with the Head of Translational Sciences, London to ensure resource sharing, protocol alignment, and unified scientific standards.
• Direct all in vitro and in vivo biology operations in Cambridge, MA through a network of CROs to generate, ingest and interpret high quality experimental data efficiently to support all aspects of our drug design programs from HitID through to IND.
• Foster a site culture of high accountability, rapid iteration, and scientific curiosity.
• Serve as a key internal consultant and advisor for global target discovery, providing critical technical assessment, feasibility analysis, and translational "stress testing" for new targets under consideration.
• Collaboratively execute program progression and determine resource allocation.
• Facilitate the transfer best practices and know-how between the UK and US sites to maximize R&D efficiency.
• Manage relationships with CROs and academic collaborators to extend the site’s internal capabilities.

Skills and qualifications 

Essential:

• PhD in relevant Biological Sciences.
• Solid foundation in Translational Sciences with a minimum of 10+ years previous industrial experience within a pharma/biotech/CRO setting, with a clear trajectory of increasing responsibility. 
• Proven track record of successfully navigating the discovery to IND transition, demonstrating mastery of molecular mechanisms.
• Track record of delivering multiple programs by formulating and implementing fit for purpose biological strategies to progress from hit ID through to IND as a program biology lead.
• Demonstrated experience in line management, mentorship, and developing scientific talent.
• Excellent strategic thinking, problem-solving, and decision-making capabilities applied to complex drug discovery challenges.
• Ability to work with computational biologists to define and implement patient and biomarker selection strategies
• Experience of working with and closely managing CRO resource. 
• Strong track record of scientific achievement, evidenced by publications, patents, and presentations.
• Genuine passion for drug discovery and enthusiasm for the potential of AI/ML to transform the field.

Nice to have:

• Experience working in an AI/ML led drug discovery environment.
• Experience of  working with product /data scientist to build or configure data analysis systems for diverse  program datasets but specifically for pharmacological data.
• Experience of diverse chemical modalities e.g. molecular glues.

Your impact 

You will be working on our groundbreaking platform that will transform the biopharmaceutical world as we know it. You'll join our Platform group, where you partner with leading engineers, scientists and ML researchers to build the critical foundations driving that transformation.

You'll be working as part of a small and highly efficient team on all parts of cloud infrastructure and software lifecycle.

We believe Isomorphic is best of both worlds: a dynamic startup where things happen fast with a secure Alphabet backing and a long-term vision.

We’re still at a relatively early stage in our journey, with a level of ambiguity as we continuously learn from each other, so you will need to build on your previous experience and show initiative in order to fully carve out your contribution in this newly created role.

What you will do 

• Design, operate, manage and refine research, development, and production cloud infrastructure (GCP, K8s, Docker, Terraform, Kapitan, etc.)
• Develop and manage tools and processes to enhance software development practices
• Contribute to core technical decisions (e.g. choice of tooling, infrastructure, and architectural design)
• Partner and collaborate with a diverse set of teams including science (drug discovery), research (machine learning), product, business development and operations

Skills and qualifications 

Essential:

• Strong experience with Docker, Terraform and at least one major Cloud Platform
• Proficiency in identifying and mitigating security risks
• Hands on experience partnering with the internal security team to work on securing the internal platforms 
• Strong hands-on experience managing Kubernetes clusters
• Clear understanding of Infrastructure as Code
• Extensive experience with modern DevOps (CI/CD, release management, automation)
• Experience with Helm/Kustomize/Kapitan or similar deployment tools
• Experience with Grafana/Prometheus/Splunk or similar monitoring/observability technologies
• Strong Python programming
• Ability to independently deliver solutions and work effectively in cross-functional teams

Nice to have:

• Experience with Google Cloud Platform (GCP)
• Experience supporting machine learning cloud infrastructure
• Experience with GitHub Actions
• Strong foundations in software engineering before moving into a technical operations role

Your impact 

As Isomorphic Labs accelerates its pipeline, we are approaching a critical inflection point: developing capabilities to deliver Iso’s ambition of multiple drug candidates per year. We are looking for a highly tactical and strategic Technical Program Manager to anchor this process.

You will play a pivotal role in operationalising our path to the clinic, managing the complex sequencing of our first IND submissions. You will be the bridge between our scientific breakthroughs and regulatory reality, ensuring that our data management and documentation mature from research-grade to submission-ready standards. This is an opportunity for a "hands on" operator who can manage detailed logistics today, with the scope to grow as our development portfolio scales.

What you will do 

• Drive non-clinical IND needs: You will manage the timeline and sequencing of late-stage discovery including CMC, DMPK, pharmacology and tox reporting to enable successful submission, ensuring no critical path items are missed. You will partner closely with counterparts in our clinical team to ensure non-clinical and clinical aspects of the IND are integrated correctly.
• Program Management: Create and maintain rigorous project plans that monitor sequencing in a highly detailed way. You will track dependencies across multiple workstreams to ensure alignment with submission goals, including working with a network of external vendors and collaborators and managing large budgets.
• Data Management: Play a leading role in the transition of document and data management workflows from general cloud storage (e.g., Google Drive) to submission-ready systems. You will ensure our data integrity and documentation meet the regulatory standards required for development.
• Cross-Functional Coordination: Act as the operational hub for interdisciplinary teams, facilitating seamless communication between scientific teams, technical operations, and regulatory consultants to keep programs on track. 
• Risk Mitigation: Proactively identify and document risks in the pre-clinical phase and devise mitigation strategies in partnership with Program Leads before they impact timelines. 
• Operational Excellence: Partner with the DDMR Leads to refine the operating model for pre-clinical development, helping to establish the world class infrastructure required for future programs.

Skills and qualifications 

Essential:

• You must have a proven track record of managing an IND application process from late discovery/pre-clinical all the way through to submission. 
• Deep experience working at the intersection of discovery and early development; you understand the specific scientific and operational shifts that occur during this transition.
• Experience implementing or managing regulatory-compliant document management systems.  
• Experience working with external vendors and collaborators.
• Experience managing large budgets.
• You have the ability to be "in the weeds" managing complex schedules and logistics, while possessing enough industry experience to provide high-level strategic input on regulatory hurdles.
• Exceptional organisational skills with a mastery of sequencing complex, multi-disciplinary activities.

Nice to have:

• Scientific MSc or PhD in Biology, Chemistry/protein engineering, toxicology or a related discipline.
• Formal program management qualification (e.g., PMP, PRINCE2) 
• Experience in a high-growth Biotech or TechBio environment
• Experience working on multiple modalities (small molecules, biologics, …) 

Your impact 

As a Senior Security Engineer, you will architect and manage the security of our groundbreaking ML-based platform and High Performance Computing (HPC) infrastructure. This role requires a highly proactive problem-solver who enjoys a fast-paced environment and possesses the curiosity to dive into diverse technical challenges. 

You will act as a versatile, T-shaped engineer, overseeing security solutions from initial requirement gathering to final implementation. By combining deep technical know-how with strong collaborative skills, you will ensure our security posture evolves as quickly as our research, managing the end-to-end lifecycle of our defense systems.

What you will do

• Secure Architecture and Product Engineering: Participate in the design and perform security reviews of our evolving AI platforms and underlying HPC infrastructure.
• Infrastructure as Code (IaC) Security: Partner with our DevOps / SRE team to harden our cloud infrastructure and our network, ensuring security by design, automation and auditability through Policy as Code.
• Third Party Systems Secure Integration: Perform deep-dive technical assessments of third-party platforms, AI solutions, Cloud or SaaS providers and support secure integration or deployment.
• Secure CI/CD: Design and implement automated security controls within our CI/CD pipelines to ensure code is secure from commit to production without slowing down research velocity.
• Threat Modeling & Risk Assessment: Conduct proactive threat modeling and risk assessment, support teams in the implementation of remediation plan and audit expected outcomes.
• Incident Response: Act as a L2/L3 escalation point for the remediation of complex vulnerabilities and security incidents.
• Identity & Access Management: Implement our state-of-the-art Zero Trust framework, ensuring robust access control and consistent enforcement of the principle of least privilege.
• Risk Management and Compliance Automation: Bridge the gap between technical controls and regulatory requirements (GDPR, GxP, EU AI Act) by automating evidence collection and risk posture monitoring (CSPM).
• Security Tooling Development: Build or integrate custom internal tools that automate repetitive security tasks, shifting our operational load from manual toil to scalable engineering.
• End-to-End Solution Delivery: Manage the full lifecycle of security controls, from initial user needs analysis and requirements gathering to structured testing and phased implementation and communication, ensuring high-quality deployment followed by data-driven continuous improvement.

Skills and qualifications 

Essential

• Cloud Engineering Proficiency: Deep technical knowledge of cloud platform security (GCP preferred) including Network and VPC design, IAM policy construction, Cloud resources hardening and Cloud native security services.
• Analytical Risk Management and Problem Solving: Proficiency in assessing multi-faceted risks and decomposing complex security issues into manageable tasks and providing data-driven recommendations to stakeholders.
• Coding Skills: Ability to write small production-grade code (e.g. in Python) and to automate security tasks, build custom tooling, etc.
• DevSecOps Tooling: Hands-on experience with Infrastructure as Code (Terraform) and version control systems (GitHub) to manage security configurations.
• Container Security: Proven ability to secure containerized workloads (Kubernetes/Docker), focusing on image signing, runtime protection, and orchestration security.
• Network Security Fundamentals: Solid understanding of modern networking, including zero-trust architecture, encryption in transit (TLS/mTLS), and API gateway security.
• Identities and Access Management: Proficiency in implementing a state of the art IAM strategy both from an organisational and technical standpoints in a multi-tenant cloud environment.
• Collaborative Security Culture: Strong ability to support researchers in AI and Drug Discovery, leveraging excellent listening skills, to provide pragmatic advice that balances high-security requirements with business agility.
• Adaptability & Communication: Excellent soft skills with the ability to navigate an ambiguous, high-growth environment and explain technical risks to non-security audiences.
• Offensive Mindset: Strong understanding of the MITRE ATT&CK framework and the ability to think like an adversary to identify "blind spots" in our defense.

Nice to have

• AI/ML Security Interest: Familiarity with the unique security challenges of an AI first company and other common AI solutions such as LLMs.
• Regulated Industry Experience: Prior experience working in BioTech, Pharma where data integrity and regulatory compliance are paramount.
• Advanced Security Certifications: Holding industry-recognized credentials such as GSE, OSCP, CISSP or professional-level Cloud Security Engineer certifications.
• Application Security (AppSec): Experience with SAST/DAST/SCA tools and a strong understanding of the OWASP Top 10 vulnerabilities.
• Zero Trust Implementation: Past success in transitioning an organization away from traditional perimeter-based security toward a mature Zero Trust model.
• SecOps Maturity: Experience building or scaling a Security Operations Center (SOC) or a Modern Detection and Response (MDR) function.
• Collaboration Tool Mastery: Advanced experience securing and automating SaaS. In particular, Google Workspace, the Atlassian stack (Jira/Confluence), Slack.
• Bio-Pharma Experience: Prior exposure to GxP validation, clinical trial data protections, or the nuances of Lab-IT security.
• Privacy Engineering: Knowledge of PETs (Privacy Enhancing Technologies) like differential privacy or homomorphic encryption.

Senior/ Principal Software Engineer, ML Ops

Your Impact

We are building the largest foundation models in biotech and applying them immediately to cure disease. You will play a pivotal role in ensuring the reliability and scalability of the foundations that make this possible.

As a Principal Engineer, you will lead the efforts to harden our systems, ensuring our groundbreaking AI is built on an unshakeable base, working closely with the research team and the Applied ML teams to ensure the infrastructure is stable, reliable and can operate with more data and larger models as we grow. 

What You Will Do

• Develop and operate our inference platform, serving fleets of cutting-edge machine learning models to scientific applications.
• Design strategy and build roadmaps for maturing the platform.
• Architect and optimize our next-generation inference services. You will solve core scaling limits, ensuring high-throughput performance and feature parity across our model serving stack.
• Contribute to core technical decisions on tooling and architectural design while partnering with science, product, and operations teams to align infrastructure with biotech R&D cycles.
• Deliver high-quality and well-tested user-focused features.

Skills and Qualifications

Essential:

• Proven experience in architecting and managing large-scale AI/ML workloads in a production environment.
• Expertise in cloud compute design, specifically within Google Cloud Platform (GCP).
• Orchestration: Significant experience deploying and managing complex workloads within Kubernetes (GKE).
• Professional familiarity with NVIDIA GPU generations and the intricacies of high-performance compute.
• Strong programming skills and a "reliability-first" approach to software development.

Nice to Have:

• A career history that spans both ML Software Engineering and Infrastructure SRE roles.
• Experience leading multi-disciplinary projects and navigating complex stakeholder requirements in a fast-paced environment.
• Familiarity with workload scheduling, ML efficiency research, and hardware benchmarking.
• Experience with Google TPU generations and specialized ML-driven R&D cycles.

About the Computational Drug Design Team

We are building a dynamic team of Computational Chemists in Cambridge, MA within the Drug Design and Medical Research function. We drive the computational chemistry strategy for our internal portfolio and collaboration projects. Crucially, we partner closely with our AI/ML colleagues, using our domain expertise to augment the Isomorphic Labs Drug Design Engine and leverage its power to accelerate drug design. We foster a supportive, learning-focused environment where every member is valued, and continuous professional development is a priority.

Your Impact

As part of our expansion to Cambridge, MA, we are seeking an experienced and strategic Head of Computational Drug Design to join our foundational Drug Design team. This is a pivotal role for a motivated scientific leader eager to shape the future of drug discovery at the intersection of computational chemistry and artificial intelligence. This role requires a unique blend of deep scientific expertise and the ability to lead both technical projects and high-performing teams, whilst contributing to or leading active drug discovery programs.

You will provide scientific leadership and strategic direction for the Computational Drug Design team, responsible for delivery and guidance of projects to clinical candidate nomination. Additionally, you will oversee and mentor a team of talented Computational Drug Designers, fostering their scientific growth and career development. Working alongside world-leading AI Scientists, you will play a critical role in establishing principles for embedding AI/ML into modern computational chemistry workflows, ensuring seamless integration across ML, Biology, and Chemistry teams.  You will partner with our Head of Chemistry, Drug Design to champion the drug discovery pipeline, overseeing external collaborations (with CROs) and lead programs to deliver critical go/no-go milestones. Critical to this role will be the ability to build highly effective and efficient connectivity with Medicinal Chemistry, Biology and Pre-Clinical Development teams to accelerate pace to the clinic. If you are a skilled Computational Chemist with leadership experience and a passion for applying cutting-edge technology to complex scientific challenges, this role offers an unparalleled opportunity for impact and growth.

What you will do 

• Apply your knowledge and track record of modern drug design and discovery principles to deliver our Drug Design portfolio. 
• Provide direct line management for a growing team of Computational Chemists. Set clear goals, provide regular feedback, support their professional development, and foster a collaborative and high-performance team environment.
• Provide strategic input and technical direction to our AI/ML platform teams. 
• Collaborate both internally and with third party organisations, interacting within multidisciplinary teams, to support data-driven delivery of high quality scientific solutions to complex technical problems. 
• Represent the company externally, interacting with existing and prospective collaborators and Contract Research Organizations (CROs). 
• Prepare detailed scientific proposals and reports to support new and ongoing programs. 
• Embrace and champion our culture of inclusion and continuous professional development.

Skills and Qualifications

Essential:

• PhD in Computational Chemistry, Medicinal Chemistry, Synthetic Chemistry, or a related scientific field, or equivalent industrial experience.
• Solid foundation in computational chemistry with a minimum of 10+ years previous industrial experience within a pharma/biotech/CRO setting.
• Proven experience leading computational chemistry strategy and execution for multiple drug discovery programs and target classes, and managing high-performing scientific teams.
• Prior experience of leading drug discovery programs, from hit finding to lead optimisation and candidate selection.
• Strong expertise in virtual screening, ligand and structure-based drug design using physics-based and ideally AI/ML methods.
• Proven track record of developing models using ML or deep learning methods.
• Expertise in writing and implementing Python scripts for analysis and tool development, and/or utilising pipelining tools to support cheminformatics and design workflows.
• Genuine passion and enthusiasm for applying AI/ML to drug design and how this can transform the field.
• Demonstrated success managing external collaborations (industry/CROs) and working effectively in cross-functional environments.
• Growth mindset, adaptability, and eagerness to learn new concepts and techniques.

Nice to Have:

• Prior experience leveraging machine learning and generative AI methods for hit finding (e.g. ultra-large virtual screening and active learning), molecular design and lead optimisation
• Strong knowledge of drug design principles, including ADMET and DMPK.
• Knowledge of modalities such as PROTACs, molecular glues, PPI inhibitors or ADCs.
• A track record of authorship of relevant scientific manuscripts.

About the Medicinal Drug Design Team

We are building a dynamic team of Medicinal Chemists in Cambridge, MA, to transform how drugs are designed. By partnering deeply with our AI/ML colleagues, we are doing more than just leveraging the Isomorphic Labs Drug Design Engine - we are actively shaping it. We use our domain expertise to challenge and refine our algorithms, creating a powerful symbiotic relationship that drives our internal and collaborative portfolios. Our team work closely together in a supportive environment, where everyone is valued for their medicinal chemistry expertise and experience they bring to the group. We have a strong growth mindset and prioritise continued development and learning.

Your impact 

As part of our expansion to Cambridge, MA, we are seeking an experienced and strategic Head of Chemistry, Drug Design to join our foundational Drug Design team. This is a pivotal role for a motivated scientific leader who is eager to shape the future of drug discovery at the intersection of medicinal chemistry and artificial intelligence. This role requires a unique blend of deep scientific expertise and the ability to lead both technical projects and high-performing teams, whilst contributing to or leading active drug discovery programs.

You will provide scientific leadership and strategic direction for the Medicinal Drug Design team, responsible for delivery and guidance of projects to clinical candidate nomination. Additionally, you will oversee and mentor a team of talented Medicinal Chemists, fostering their scientific growth and career development. Working alongside world-leading AI/ML Scientists, you will play a critical role in driving project success, enhancing our AI platform through expert feedback, and building a high-performing team. Critical to this role will be the ability to build highly effective and efficient connectivity with Computational Drug Design, Biology and Pre-Clinical Development teams to accelerate pace to the clinic. If you are a skilled Medicinal Chemist with leadership experience and a passion for applying cutting-edge technology to complex scientific challenges, this role offers an unparalleled opportunity for impact and growth.

What you will do 

• Apply your knowledge and track record of modern drug design & discovery principles to deliver our Drug Design portfolio. 
• Provide direct line management for a growing team of Medicinal Chemists. Set clear goals, provide regular feedback, support their professional development, and foster a collaborative and high-performance team environment.
• Provide strategic input and technical direction to our AI/ML platform teams. 
• Collaborate both internally and with third party organisations, interacting within multidisciplinary teams, to support data-driven delivery of high quality scientific solutions to complex technical problems. 
• Represent the company externally, interacting with existing and prospective collaborators and Contract Research Organizations (CROs). 
• Effectively manage CRO resource and monitor KPIs to maintain delivery. 
• Prepare detailed scientific proposals and reports to support new and ongoing programs. 
• Embrace and champion our culture of inclusion and continuous professional development. 

Skills and qualifications 

Essential:

• PhD in Synthetic Organic Chemistry, Medicinal Chemistry or a related technical field, or equivalent industrial experience.
• Solid foundation in medicinal chemistry with a minimum of 10+ years previous industrial experience within a pharma/biotech/CRO setting. 
• Proven track record of leading medicinal chemistry efforts on drug discovery projects, demonstrating significant contributions to project progression (ideally from Hit Identification through to Lead Optimization/Candidate Nomination, with familiarity of optimization of Drug Metabolism and Pharmacokinetics (DMPK).
• Demonstrated experience in line management, mentorship, and developing scientific talent.
• Excellent strategic thinking, problem-solving, and decision-making capabilities applied to complex drug discovery challenges.
• Strong strategic thinking, problem-solving, and decision-making capabilities applied to complex drug discovery challenges.
• Experience of working with and closely managing CRO resource. 
• Strong track record of scientific achievement, evidenced by publications, patents, and presentations.
• Genuine passion for drug discovery and enthusiasm for the potential of AI/ML to transform the field.

Nice to have:

• Experience of successful application of fragment-based drug design approaches. 

Your impact

We are seeking a highly technical and collaborative Senior Chemistry, Manufacturing, and Controls Project Lead to drive the development and CMC strategy for our next-generation biologics and Antibody-Drug Conjugates (ADC) pipeline. This is a high impact position at the nexus of protein design and engineering, sophisticated linker-payload chemistry and complex regulatory sciences. The role requires a candidate who can navigate the unique challenges of multi-part drug substances and harmonise them into a stable, scalable therapeutic.

As the CMC Lead, you will serve as the technical expert for our diverse portfolio of computationally designed therapeutic candidates. This is a high-impact leadership role responsible for building the bridge between Isomorphic’s AI-driven discovery engine and the physical manufacturing of clinic-ready drugs.

You will design the CMC strategy for a variety of complex biologics and multi-specifics. You will oversee the end-to-end technical development, from cell line optimisation and sophisticated upstream/downstream processing to the precision chemistry required for advanced conjugation and assembly. We are looking for a visionary who thrives at the intersection of biology and chemistry, capable of navigating the unique CMC hurdles of next-generation modalities while ensuring a robust, scalable path to the clinic:

What you will do

• Design and oversee end-to-end manufacturing frameworks for a diverse portfolio of novel scaffolds and functionalized antibodies. This includes orchestrating cell line development, advanced upstream/downstream biologics processing, and the precision molecular assembly or conjugation steps required for next-generation therapeutic formats.
• Lead the optimization of site-specific modification and coupling chemistries (e.g., conventional and novel conjugation). You will drive strategies to achieve precise stoichiometry (including Drug-to-Antibody Ratios) and structural homogeneity while minimizing product-related impurities and "off-target" modifications.
• Lead the selection and technical oversight of global Contract Development and Manufacturing Organizations. You will manage complex tech transfers, audit Master Batch Records, and troubleshoot manufacturing deviations for both the biologic intermediates and the final multi-component drug products.
• Define the Analytical Target Profile for designed complex molecules. You will ensure the structural integrity, folding, and stability of integrated linkers, payloads, or auxiliary domains under physiological and accelerated stress conditions.
• Act as the primary author for CMC sections of global regulatory filings (IND/IMPD/BLA). You will develop and defend the control strategy for both the primary biologic and any high-potency or chemically synthesized components, ensuring alignment with global health authority expectations for novel modalities.

Skills and qualifications 

Essential:

• PhD or MSc in Biochemistry, Chemical Engineering, Chemistry, or a related biopharmaceutical field.
• 8+ years (or 5+ for high-growth) of professional experience in biologics CMC, with a proven track record of moving complex modalities from late-stage discovery into clinical manufacturing.
• Experience with a diverse range of next-gen scaffolds, such as bispecific antibodies, nanobodies (VHH), or cytotoxic and non-cytotoxic/novel payload delivery systems.
• Direct, hands-on experience in the development, scale-up, or manufacturing of Antibody-Drug Conjugates (ADCs) or other chemically modified biologics.
• Deep knowledge of analytical techniques required for multi-component molecules, including Drug-to-Antibody Ratio (DAR) determination and advanced peptide mapping/MS-based characterization.
• Strong practical knowledge of cGMP and global regulatory guidelines (FDA/EMA), specifically as they apply to combination products and biotechnological intermediates.

Nice to have:

• Experience of working with ML models for biologics design
• Experience of developing or using AI tools (LLM) to accelerate CMC processes including reporting.

Research Scientist (Machine Learning), Lausanne

Your impact 

As a Research Scientist in machine learning (ML), you will play an exciting role in building greenfield machine learning based models and algorithms that will power our platform to transform the drug discovery world as we know it. 

Working in a highly creative, fast-paced and interdisciplinary environment, you will be partnering with leading engineers and scientists to conceive, design, and develop cutting edge machine learning algorithms to unlock new modelling and predictive power which will be critical to the organisation’s success. You will draw upon your existing deep research experience whilst learning from those around you, to apply novel techniques and ideas to newly encountered computational biology and chemistry problems.

Depending on your experience:

You will create and lead projects, bringing together a variety of disciplined scientists and engineers to pursue some of the most ambitious modelling problems with deep learning - as well as providing technical mentorship and people management for others in the ML community at Isomorphic Labs

You will be instrumental in leading greenfield machine learning based research projects, building the models, and algorithms that will power our platform to transform the drug discovery world as we know it.

What you will do

• Contribute to our research directions in machine learning by using your extensive knowledge of the field to apply world-leading ML algorithms to drug discovery.
• Identify and create novel ML techniques and the required data to train.
• Develop the architectures and training algorithms of machine learning models.
• Analyse and tune experimental results to inform future experimental directions.
• Implement and scale training and inference engineering frameworks.
• Report and present research findings and developments clearly and efficiently, to both other ML scientists and scientists of different disciplines.
• Iterate collaboratively with scientists and domain experts, sharing your own domain experience.
• Suggest and engage in team collaborations to meet ambitious research goals.
  
  Depending on your experience:
• Provide technical mentorship and guidance to the ML research community, advising on projects, and shaping our research roadmap based on your deep technical expertise.
• Provide developmental support to other ML research scientists.
• Create, lead, and run ML research projects, fostering collaborative and diverse teams to solve high priority modelling problems.Cultivate a diverse and inclusive research culture.

Skills and qualifications 

Essential

• PhD or equivalent practical experience in a technical field.
• A proven track record in machine learning using deep learning techniques, including designing new architectures, hands-on experimentation, analysis, and visualisation.
• Strong knowledge of linear algebra, calculus and statistics.
• Experience using ML frameworks such as JAX, PyTorch, or TensorFlow, and scientific software such as NumPy, SciPy, or Pandas.
• A passion for applying ML research to real world problems.
• Depending on your experience: project supervision, leadership, or management.

Nice to have

• PhD in machine learning or computer science.
• Relevant research experience to the position such as post doctoral roles, a proven track record of publications, or contributions to machine learning codebases.
• Experience working in a scientific environment across disciplines (particularly biology, chemistry, physics).
• Experience working with biological or chemical data and biological or chemistry software.
• Experience working with real-world datasets.
• Experience with ML on accelerators.
• Experience in any of: large scale deep learning, generative models, graph neural networks, deep learning for drug discovery, deep learning for computer vision, 3D graphics/robotics, real-world applied RL.

Your impact 

As a Senior Security Engineer, you will architect and manage the security of our groundbreaking ML-based platform and High Performance Computing (HPC) infrastructure. This role requires a highly proactive problem-solver who enjoys a fast-paced environment and possesses the curiosity to dive into diverse technical challenges. 

You will act as a versatile, T-shaped engineer, overseeing security solutions from initial requirement gathering to final implementation. By combining deep technical know-how with strong collaborative skills, you will ensure our security posture evolves as quickly as our research, managing the end-to-end lifecycle of our defense systems.

What you will do

• Secure Architecture and Product Engineering: Participate in the design and perform security reviews of our evolving AI platforms and underlying HPC infrastructure.
• Infrastructure as Code (IaC) Security: Partner with our DevOps / SRE team to harden our cloud infrastructure and our network, ensuring security by design, automation and auditability through Policy as Code.
• Third Party Systems Secure Integration: Perform deep-dive technical assessments of third-party platforms, AI solutions, Cloud or SaaS providers and support secure integration or deployment.
• Secure CI/CD: Design and implement automated security controls within our CI/CD pipelines to ensure code is secure from commit to production without slowing down research velocity.
• Threat Modeling & Risk Assessment: Conduct proactive threat modeling and risk assessment, support teams in the implementation of remediation plan and audit expected outcomes.
• Incident Response: Act as a L2/L3 escalation point for the remediation of complex vulnerabilities and security incidents.
• Identity & Access Management: Implement our state-of-the-art Zero Trust framework, ensuring robust access control and consistent enforcement of the principle of least privilege.
• Risk Management and Compliance Automation: Bridge the gap between technical controls and regulatory requirements (GDPR, GxP, EU AI Act) by automating evidence collection and risk posture monitoring (CSPM).
• Security Tooling Development: Build or integrate custom internal tools that automate repetitive security tasks, shifting our operational load from manual toil to scalable engineering.
• End-to-End Solution Delivery: Manage the full lifecycle of security controls, from initial user needs analysis and requirements gathering to structured testing and phased implementation and communication, ensuring high-quality deployment followed by data-driven continuous improvement.

Skills and qualifications 

Essential

• Cloud Engineering Proficiency: Deep technical knowledge of cloud platform security (GCP preferred) including Network and VPC design, IAM policy construction, Cloud resources hardening and Cloud native security services.
• Analytical Risk Management and Problem Solving: Proficiency in assessing multi-faceted risks and decomposing complex security issues into manageable tasks and providing data-driven recommendations to stakeholders.
• Coding Skills: Ability to write small production-grade code (e.g. in Python) and to automate security tasks, build custom tooling, etc.
• DevSecOps Tooling: Hands-on experience with Infrastructure as Code (Terraform) and version control systems (GitHub) to manage security configurations.
• Container Security: Proven ability to secure containerized workloads (Kubernetes/Docker), focusing on image signing, runtime protection, and orchestration security.
• Network Security Fundamentals: Solid understanding of modern networking, including zero-trust architecture, encryption in transit (TLS/mTLS), and API gateway security.
• Identities and Access Management: Proficiency in implementing a state of the art IAM strategy both from an organisational and technical standpoints in a multi-tenant cloud environment.
• Collaborative Security Culture: Strong ability to support researchers in AI and Drug Discovery, leveraging excellent listening skills, to provide pragmatic advice that balances high-security requirements with business agility.
• Adaptability & Communication: Excellent soft skills with the ability to navigate an ambiguous, high-growth environment and explain technical risks to non-security audiences.
• Offensive Mindset: Strong understanding of the MITRE ATT&CK framework and the ability to think like an adversary to identify "blind spots" in our defense.

Nice to have

• AI/ML Security Interest: Familiarity with the unique security challenges of an AI first company and other common AI solutions such as LLMs.
• Regulated Industry Experience: Prior experience working in BioTech, Pharma where data integrity and regulatory compliance are paramount.
• Advanced Security Certifications: Holding industry-recognized credentials such as GSE, OSCP, CISSP or professional-level Cloud Security Engineer certifications.
• Application Security (AppSec): Experience with SAST/DAST/SCA tools and a strong understanding of the OWASP Top 10 vulnerabilities.
• Zero Trust Implementation: Past success in transitioning an organization away from traditional perimeter-based security toward a mature Zero Trust model.
• SecOps Maturity: Experience building or scaling a Security Operations Center (SOC) or a Modern Detection and Response (MDR) function.
• Collaboration Tool Mastery: Advanced experience securing and automating SaaS. In particular, Google Workspace, the Atlassian stack (Jira/Confluence), Slack.
• Bio-Pharma Experience: Prior exposure to GxP validation, clinical trial data protections, or the nuances of Lab-IT security.
• Privacy Engineering: Knowledge of PETs (Privacy Enhancing Technologies) like differential privacy or homomorphic encryption.

About the Medicinal Drug Design Team

We are a dynamic team of Medicinal Chemists transforming how drugs are designed. By partnering deeply with our AI/ML colleagues, we are doing more than just leveraging the Isomorphic Labs drug design engine - we are actively shaping it. We use our domain expertise to challenge and refine our algorithms, creating a powerful symbiotic relationship that drives our internal and collaborative portfolios. Our team work closely together in a supportive environment, where everyone is valued for their medicinal chemistry expertise and experience they bring to the group. We have a strong growth mindset and prioritise continued development and learning.

Your impact 

As part of the ongoing expansion of our Drug Design and Medical Research function, we are hiring Medicinal Drug Design Leads. You will work as a Chemistry Lead, delivering scientific expertise and strategic direction to fulfil milestone objectives on our portfolio projects. You will support the business alongside world leading AI/ML Drug Design Platform teams, and will work collaboratively to drive improvements in the platform and apply these to impactful drug design projects. Please note that this is a scientific leadership role, where you will take an active hands-on role as an individual contributor rather than being a people manager, although you will support and mentor junior colleagues.

If you are a skilled Medicinal Chemist with a passion for applying cutting-edge technology to complex scientific challenges, this role offers an unparalleled opportunity for impact and growth.

What you will do 

• Invent new medicines. Rapidly drive drug discovery programs to value inflection points by deploying your knowledge of modern discovery principles and synthetic organic chemistry, taking ownership as a Medicinal Chemistry Lead.
• Collaborate cross-functionally to support the data-driven delivery of high quality scientific solutions to complex technical problems.
• Represent the company externally, interacting with existing and prospective collaborators and Contract Research Organisations (CROs).
• Provide strategic input and technical direction to our AI/ML platform teams.
• Effectively manage CRO resource and monitor KPIs to maintain delivery.
• Prepare detailed scientific proposals and reports to support new and ongoing programs. 
• Embrace and champion our culture of inclusion and continuous professional development.

Skills and qualifications 

Essential:

• PhD in Medicinal Chemistry, Synthetic Organic Chemistry, or a related technical field, or equivalent industrial experience.
• 5+ years’ professional experience in a Medicinal Chemistry role, operating within a biotech, pharma or CRO setting.
• Proven track record of leading medicinal chemistry efforts on drug discovery projects, demonstrating significant contributions to project progression (ideally from hit identification through to lead optimisation/candidate nomination), with familiarity of optimisation of DMPK.
• Experience of contributing to structure-based drug design problems. 
• Excellent strategic thinking, problem-solving, and decision-making capabilities applied to complex drug discovery challenges.
• Experience of working with and closely managing CRO resources. 
• Strong track record of scientific achievements, evidenced by publications, patents, and presentations.
• A genuine passion for drug discovery and enthusiasm for the potential of AI/ML to transform the field.
• Excellent communication (written and verbal) and interpersonal skills, with an ability to work effectively in a cross-functional, collaborative team environment.
• Track record of creative problem solving with a strong growth mindset, adaptability, and eagerness to learn new concepts and techniques.

Nice to have:

• Experience of successful application of fragment-based drug design approaches.

About the Medicinal Drug Design team

We are a dynamic team of Medicinal Chemists transforming how drugs are designed. By partnering deeply with our AI/ML colleagues, we are doing more than just leveraging the Isomorphic Labs drug design engine - we are actively shaping it. We use our domain expertise to challenge and refine our algorithms, creating a powerful symbiotic relationship that drives our internal and collaborative portfolios. Our team closely together in a supportive environment, where everyone is valued for their medicinal chemistry expertise and experience they bring to the group. We have a strong growth mindset and prioritise continued development and learning.

We are looking for a Team Leader, Medicinal Drug Design to champion this cross-disciplinary approach, fostering a supportive team culture where continuous learning and the adoption of next-generation tools are the standard, not the exception. This is a pivotal role for an experienced and motivated scientific leader eager to shape the future of drug discovery at the intersection of medicinal chemistry and artificial intelligence.

Your impact 

You will be responsible for line managing and mentoring a small team of talented and high-performing Medicinal Chemists, fostering their scientific growth and career development. Additionally, you will provide scientific leadership and strategic direction for key drug discovery projects, guiding them from initiation towards clinical candidate selection. Working alongside world-leading AI/ML scientists, you will play a critical role in driving project success, enhancing our AI platform through your technical expertise.

If you are a skilled Medicinal Chemist with leadership experience and a passion for applying cutting-edge technology to complex scientific challenges, this role offers an unparalleled opportunity for impact and growth.

What you will do

• Provide line management for a team of 2-4 Medicinal Chemists. Set clear goals, provide regular feedback, support their professional development, and foster a collaborative and high-performance team environment.
• Invent new medicines. Rapidly drive drug discovery programs to value inflection points by deploying your knowledge of modern discovery principles and synthetic organic chemistry, taking ownership as either a Medicinal Chemistry Lead or overall Project Lead.
• Collaborate cross-functionally to support the data-driven delivery of high quality scientific solutions to complex technical problems.
• Represent the company externally, interacting with existing and prospective collaborators and Contract Research Organisations (CROs).
• Provide strategic input and technical direction to our AI/ML platform teams.
• Effectively manage CRO resource and monitor KPIs to maintain delivery.
• Generate intellectual property positions and capture the value derived from IsoLabs’ investment.
• Prepare detailed scientific proposals and reports to support new and ongoing programs. 
• Embrace and champion our culture of inclusion and continuous professional development.
  
  

Skills and qualifications 

Essential:

• PhD in Medicinal Chemistry, Synthetic Organic Chemistry, or a related technical field, or equivalent industrial experience.
• 8+ years’ professional experience in a Medicinal Chemistry role, operating within a biotech, pharma or CRO setting.
• Proven track record of leading medicinal chemistry efforts on drug discovery projects, demonstrating significant contributions to project progression (ideally from hit identification through to lead optimisation/candidate nomination), with familiarity of optimisation of DMPK.
• Experience of contributing to structure-based drug design problems. 
• Experience of leading a high-performing scientific team, mentoring and empowering them to thrive in their roles.
• Excellent strategic thinking, problem-solving, and decision-making capabilities applied to complex drug discovery challenges.
• Experience of working with and closely managing CRO resources. 
• Strong track record of scientific achievements, evidenced by publications, patents, and presentations.
• A genuine passion for drug discovery and enthusiasm for the potential of AI/ML to transform the field.
• Excellent communication (written and verbal) and interpersonal skills, with an ability to work effectively in a cross-functional, collaborative team environment.
• Track record of creative problem solving with a strong growth mindset, adaptability, and eagerness to learn new concepts and techniques.

Nice to have:

• Experience of successful application of fragment-based drug design approaches. 

Your Impact

We are seeking a Team / Research Leader specialising in computational chemistry to spearhead the design of novel small molecule therapeutics. This role requires a unique blend of deep scientific expertise and the ability to lead both technical projects and high-performing teams, whilst contributing to or leading active drug discovery programs.

As a pivotal member of the Drug Design team, you will drive complex projects from early discovery through to candidate selection. You will leverage your expertise in strategic leadership and management of multi-program pipelines to deliver life-changing medicines using our cutting-edge AI drug design engine.


What You Will Do

• Strategic Direction: Define the core scientific and technical direction of our small molecule therapeutic programs, ensuring alignment with company goals.
• Program Leadership: Champion the drug discovery pipeline, overseeing external collaborations (with CROs) and leading programs to meet critical go/no-go milestones.
• Innovation & Integration: Establish principles for embedding cutting-edge AI/ML into modern computational chemistry workflows, ensuring seamless integration across ML, Biology, and Chemistry teams.
• Talent Development: Foster a culture of scientific excellence by proactively mentoring, guiding, and evaluating the career development of team members.
• Technical Execution: Apply AI-first approaches to provide technical and strategic directions, and execute drug design programs.
  
  

Skills and Qualifications

Essential:

• PhD in Computational Chemistry, Medicinal Chemistry, Synthetic Chemistry, or a related scientific field.
• 8+ years’ professional experience in either a pharma, biotech or CRO environment working at all stages of the drug discovery process, from hit finding to lead optimisation and candidate selection.
• Proven experience leading computational chemistry strategy and execution for multiple drug discovery programs and target classes, and managing high-performing scientific teams.
• Strong expertise in virtual screening, ligand and structure-based drug design using physics-based and ideally AI/ML methods.
• Proven track record of developing QSAR models using ML or deep learning methods.
• Expertise in writing and implementing Python scripts for analysis and tool development, and/or utilising pipelining tools to support cheminformatics and design workflows.
• Strong knowledge of medicinal chemistry principles including ADMET and DMPK.
• Genuine passion and enthusiasm for applying AI/ML to drug design and how this can transform the field.
• Demonstrated success managing external collaborations (industry/CROs) and working effectively in cross-functional environments.
• Growth mindset, adaptability, and eagerness to learn new concepts and techniques.

Nice to Have:

• Prior experience leveraging machine learning and generative AI methods for hit finding (e.g. ultra-large virtual screening and active learning), molecular design and lead optimisation (e.g. REINVENT, cofolding and AI-powered ligand/pose scoring methods).
• Prior experience of leading drug discovery programs.
• Track record of authorship of relevant scientific manuscripts.
• Knowledge of modalities such as PROTACs, molecular glues, PPI inhibitors or ADCs.

Research Scientist - Applied Large Language Models 

Your impact 

As a Research Scientist focused on the application of Large Language Models (LLMs), you will play an exciting role in bringing cutting edge technologies to bear across our research areas to transform the drug discovery world as we know it. 

Working in a highly creative, fast-paced and interdisciplinary environment, you will be partnering with leading research scientists and engineers to conceive, design, and develop cutting edge LLM applications that help to unlock new modelling capabilities and predictive power which will be critical to the organisation’s success. You will draw upon your existing deep understanding and experience whilst learning from those around you, to apply novel techniques and ideas to newly encountered computational biology and chemistry problems.

Depending on your experience:

You will both partner with teams across our existing research areas and create and lead standalone projects, bringing together a variety of disciplined scientists and engineers to pursue some of the most ambitious modelling problems through the application of LLMs - as well as providing technical mentorship and people management for others in the ML community at Isomorphic Labs.

You will be instrumental in leading machine learning based research projects, building the models, and algorithms that will power our platform to drive us close to achieving our ambitious mission to one day solve all disease with the help of AI.

What you will do

• Contribute to core research in machine learning by pushing the boundaries of Large Language Models in their application to the world of drug discovery
• Develop and refine LLM-driven approaches for multiple use cases across our research areas, using your extensive knowledge of the field to modify and apply models and explore their capabilities when applied to complex biological and medical challenges.
• Identify and create novel ML techniques and the required data to train and apply models
• Analyse and tune experimental results to inform future experimental directions.
• Implement and scale training and inference engineering frameworks
• Report and present research findings and developments clearly and efficiently, to both other ML scientists and scientists of different disciplines
• Iterate collaboratively with scientists and domain experts, sharing your own domain experience
• Suggest and engage in team collaborations to meet ambitious research goals
  
  Depending on your experience:
• Provide technical mentorship and guidance to the ML research community, advising on projects, and shaping our research roadmap based on your deep technical expertise.
• Provide developmental support to other ML research scientists.
• Create, lead, and run ML research projects, fostering collaborative and diverse teams to solve high priority modelling problems. Cultivate a diverse and inclusive research culture.

Skills and qualifications 

Essential

• PhD or equivalent practical experience in a technical field
• Highly specialized LLM builder with a passion for, and strong experience in, applying LLMs to novel problem spaces
• Deep understanding and experience of model architectures, training methods, and techniques for application of LLMs, including deployment for bespoke use cases and applications, established experience in post-training, reasoning, test-time scaling, tool-use, alignment, agents, LLM research, as well as reinforcement learning and fine-tuning 
• Strong knowledge of linear algebra, calculus and statistics.
• Experience using ML frameworks such as JAX, PyTorch, or TensorFlow, and scientific software such as NumPy, SciPy, or Pandas.
• Depending on your experience: project supervision, leadership, or management.
• Strong knowledge of LLM landscape today, and likely developments for the near future
• Experience working with real-world datasets.

Nice to have

• PhD in machine learning or computer science.
• Relevant research experience to the position such as post doctoral roles, a proven track record of publications, or contributions to machine learning codebases.
• A strong background in biology or medicine, enabling you to bridge the gap between advanced AI capabilities and complex scientific problems in drug discovery
• Experience working in a scientific environment across disciplines (particularly biology, chemistry, physics), and with real world biological or chemical datasets and biological or chemistry software
• Experience in computational chemistry, bioinformatics, or related fields would be highly beneficial, along with a track record of applying AI to real-world scientific challenges
• Experience with multi-parameter optimization
• Experience in any of: large scale deep learning, generative models, graph neural networks, deep learning for drug discovery, deep learning for computer vision, 3D graphics/robotics, real-world applied RL

Research Scientist (Machine Learning), London

Your impact 

As a Research Scientist in machine learning (ML), you will play an exciting role in building greenfield machine learning based models and algorithms that will power our platform to transform the drug discovery world as we know it. 

Working in a highly creative, fast-paced and interdisciplinary environment, you will be partnering with leading engineers and scientists to conceive, design, and develop cutting edge machine learning algorithms to unlock new modelling and predictive power which will be critical to the organisation’s success. You will draw upon your existing deep research experience whilst learning from those around you, to apply novel techniques and ideas to newly encountered computational biology and chemistry problems.

Depending on your experience:

You will create and lead projects, bringing together a variety of disciplined scientists and engineers to pursue some of the most ambitious modelling problems with deep learning - as well as providing technical mentorship and people management for others in the ML community at Isomorphic Labs

You will be instrumental in leading greenfield machine learning based research projects, building the models, and algorithms that will power our platform to transform the drug discovery world as we know it.

What you will do

• Contribute to our research directions in machine learning by using your extensive knowledge of the field to apply world-leading ML algorithms to drug discovery.
• Identify and create novel ML techniques and the required data to train.
• Develop the architectures and training algorithms of machine learning models.
• Analyse and tune experimental results to inform future experimental directions.
• Implement and scale training and inference engineering frameworks.
• Report and present research findings and developments clearly and efficiently, to both other ML scientists and scientists of different disciplines.
• Iterate collaboratively with scientists and domain experts, sharing your own domain experience.
• Suggest and engage in team collaborations to meet ambitious research goals.
  
  Depending on your experience:
• Provide technical mentorship and guidance to the ML research community, advising on projects, and shaping our research roadmap based on your deep technical expertise.
• Provide developmental support to other ML research scientists.
• Create, lead, and run ML research projects, fostering collaborative and diverse teams to solve high priority modelling problems.Cultivate a diverse and inclusive research culture.

Skills and qualifications 

Essential

• PhD or equivalent practical experience in a technical field.
• A proven track record in machine learning using deep learning techniques, including designing new architectures, hands-on experimentation, analysis, and visualisation.
• Strong knowledge of linear algebra, calculus and statistics.
• Experience using ML frameworks such as JAX, PyTorch, or TensorFlow, and scientific software such as NumPy, SciPy, or Pandas.
• A passion for applying ML research to real world problems.
• Depending on your experience: project supervision, leadership, or management.

Nice to have

• PhD in machine learning or computer science.
• Relevant research experience to the position such as post doctoral roles, a proven track record of publications, or contributions to machine learning codebases.
• Experience working in a scientific environment across disciplines (particularly biology, chemistry, physics).
• Experience working with biological or chemical data and biological or chemistry software.
• Experience working with real-world datasets.
• Experience with ML on accelerators.
• Experience in any of: large scale deep learning, generative models, graph neural networks, deep learning for drug discovery, deep learning for computer vision, 3D graphics/robotics, real-world applied RL.