Position Summary

We are seeking a visionary, hands-on scientific leader to drive our high-throughput functional genomics discovery platform. In this role, you will collaborate closely with experimental and computational teams across Neptune, manage and develop a high-performing group of scientists and research associates, and lead the onboarding and scale-up of next-generation single-cell screening technologies. You will serve as a technical authority in genomics technologies across the organization and play a central role in enabling large-scale screening for Neptune’s discovery engine—building a unique data moat that powers rapid and continuous target identification.

The ideal candidate brings deep expertise in advanced single-cell CRISPR screening and sequencing technologies, combined with strong people leadership, project management experience, and a demonstrated ability to deliver large-scale projects under tight timelines. This role requires a highly collaborative, team-oriented mindset with a focus on generating high-quality results at speed.

About You

• Scientific expert and team leader: You bring deep expertise in advanced single-cell and CRISPR screening technologies and have a strong track record of building and mentoring high-performing scientific teams through clear goals, execution, and guidance.
• Systems thinker and process optimizer: You think naturally at scale - building  efficient workflows, and enabling large-volume research while balancing scientific rigor with operational demands.
• Results-driven: You thrive in fast-paced environments with tight deadlines, excel at prioritization, and consistently deliver complex projects on time within high-throughput settings..
• Collaborative Team-player: You enjoy leading and mentoring a team of research scientists and associates, and you excel at working across experimental, computational, and operational teams to achieve shared goals. 
• Adaptable learner: You stay current with emerging genomics technologies, apply sound judgment when adopting innovations, and can pivot strategies effectively to meet evolving organizational needs

Key Responsibilities

• Act as a key individual contributor in a highly collaborative team, providing hands-on expertise in the lab to de-risk new technologies and scale up robust workflows for our high-throughput single-cell screening platform
• Plan, manage, and execute a large-scale target discovery initiative focused on high-throughput single-cell CRISPR screening in vitro (2D and 3D) and in vivo
• Manage multiple complex projects simultaneously, ensuring timely execution under tight deadlines
• Lead, mentor, and manage a dedicated team of scientists and senior research associates, fostering a culture of innovation, collaboration, and scientific rigor
• Spearhead the identification, evaluation, and implementation of cutting-edge technologies to enhance the speed, scale, and quality of our target discovery campaigns
• Drive the design, execution, and optimization of sophisticated screening assays and technology development projects that directly impact program objectives
• Develop and champion the strategic vision for technology innovation within our target discovery platform, staying current with rapidly evolving scientific fields and identifying, evaluating, and implementing new methodologies
• Oversee experimental design, protocol development, and resource allocation across the target discovery platform to ensure project milestones and scientific objectives are met
• Effectively analyze and present data, clearly communicating research plans, progress, and timelines to the team
• Present scientific findings, project updates, and strategic proposals to internal and external stakeholders, contributing to publications and intellectual property filings
• Collaborate closely with the CompBio team to build robust screening workflows, and maintain detailed, well-organized, and timely documentation of experiments and data

Qualification and Education Requirements

You must have:

• PhD, MD, or MD/PhD in genomics, biomedical engineering, molecular biology, or a related field, with training in high-throughput single-cell methodologies and next-generation sequencing
• 3–5+ years of relevant experience in academia, biotechnology, or the pharmaceutical industry
• Prior experience in a leadership or mentorship role, with a demonstrated ability to manage and develop Ph.D. level scientists effectively
• Proven record of delivering large, complex projects under tight deadlines in fast-paced, high-throughput environments
• Demonstrated hands-on expertise and a strong, proven track record in genome engineering, CRISPR screening design, and high-throughput single-cell functional genomics
• Deep expertise in molecular biology, biomedical engineering, high-content CRISPR screening, and single-cell genomics, supported by several years of academic or industry experience
• Extensive knowledge of NGS library preparation workflows and the computational aspects of multi-omic profiling
• Experience with a wide range of biological systems, including mammalian cell culture, primary cells, and complex cellular models (e.g., 3D organoid cultures and mouse models) relevant to biologics discovery
• Experience with—or strong enthusiasm for—working at the interface of biology and data science, with the ability to collaborate effectively with AI/ML and computational scientists
• Strong problem-solving abilities and an aptitude for innovation
• Ability to adapt quickly to shifting priorities while delivering high-quality, detail-oriented results on time
• A high degree of teamwork and a collaborative mindset, along with the ability to work independently

Additional preferred experience includes:

• Industry experience post-PhD is desirable
• Experience implementing process improvements and automation in production settings
• Willingness to quickly discover and learn new methods and approaches
• High motivation, with a strong work ethic and dedication to generating impact.
• Experience with computational data handling, processing, and analysis
• Long-term personal vision with defined career goals.
• Outstanding written and verbal communication skills

Position Summary

We are seeking a Computational Research Associate to support our data analysis and infrastructure efforts across functional genomics and single-cell perturbation experiments. The ideal candidate has hands-on experience working with large biological datasets, enjoys building efficient and reproducible analysis workflows, and thrives in a collaborative, fast-paced startup environment.

You will play a central role in processing, analyzing, and organizing single-cell and perturb-seq data, maintaining and improving computational pipelines, and supporting the broader team with high-quality data outputs and infrastructure.

Key Responsibilities

• Process and analyze large-scale single-cell and perturb-seq datasets using established computational pipelines.
• Develop, document, and maintain reproducible analysis workflows and data processing infrastructure.
• Support data management and organization across multiple internal and external datasets.
• Collaborate closely with experimental and computational scientists to translate raw data into interpretable biological results.
• Implement and optimize pipelines in cloud environments (e.g., AWS, GCP) for scalable data processing.
• Maintain codebases, perform quality control on data outputs, and ensure reproducibility and traceability of analyses.
• Generate clear reports, visualizations, and summaries to communicate results across teams.

Qualification and Education Requirements

You must have:

• B.S. or M.S. in Bioinformatics, Computational Biology, Computer Science, or a related quantitative field.
• 2+ years of experience working with biological or single-cell datasets.
• Proficiency in Python and/or R for data analysis and visualization.
• Familiarity with standard genomics tools and file formats (FASTQ, BAM, HDF5, AnnData, etc.).
• Experience using and maintaining analysis pipelines in a Unix/Linux environment.
• Experience working with cloud compute platforms (AWS, GCP, or similar).
• Strong organizational skills, attention to detail, and commitment to clean, reproducible code.

Additional preferred experience includes:

• Experience analyzing single-cell RNA-seq or perturb-seq datasets.
• Familiarity with workflow management systems (Nextflow, Snakemake, or similar).
• Experience with containerization tools such as Docker.
• Exposure to data engineering concepts (e.g., databases, versioned data storage, data pipelines).
• Understanding of basic statistical methods for genomics data analysis.
•  

Position Summary

We are seeking a Computational Biologist who is passionate about using data-driven, scalable methods to reveal biological insights. The ideal candidate is an independent thinker with strong computational and quantitative skills, and the ability to collaborate closely with both experimental and computational scientists. You will design, implement, and scale computational pipelines for single-cell perturbation datasets, while contributing to model development and experimental design.

This is a unique opportunity to join a dynamic, interdisciplinary environment and help shape Neptune Bio’s computational strategy and infrastructure.

Key Responsibilities

• Develop, innovate, and maintain advanced computational methods to process, analyze, and interpret large-scale single-cell genomics and perturbation datasets.
• Collaborate with wet-lab and computational teams to integrate data from diverse experimental modalities and guide experimental design.
• Build, optimize, and scale data analysis pipelines using modern cloud computing environments (e.g., AWS, GCP, Azure).
• Contribute to Neptune Bio’s data infrastructure, ensuring reproducibility, scalability, and efficient access to large datasets.
• Stay current with advances in computational biology, machine learning, and scalable infrastructure, applying them to ongoing research challenges.
• Communicate findings clearly through reports, visualizations, and presentations to multidisciplinary audiences.

Qualification and Education Requirements

You must have:

• Ph.D. in Bioinformatics, Computational Biology, Computer Science, or a related quantitative field, OR equivalent experience (e.g., BS/MS with ≥3 years of relevant experience).
• Proficiency in Python, R, and Unix/Linux environments
• Demonstrated experience in single-cell or multi-omics data analysis.
• Solid understanding of statistics, data modeling, and modern machine learning approaches.
• Experience deploying and scaling computational pipelines on cloud platforms (AWS, GCP, or similar).
• Strong communication skills and enthusiasm for working in a collaborative, fast-paced environment.

Additional preferred experience includes:

• Background in functional genomics, CRISPR screens, or perturb-seq analysis.
• Experience integrating multi-source data to derive novel and impactful insights.
• Expertise in data engineering and reproducible research tools (e.g., Docker, Nextflow, Snakemake) as well as familiarity with cloud-native architectures and distributed compute.
• Strong publication record demonstrating innovation in computational methods or biological data analysis.
• Experience with deep learning frameworks such as PyTorch or TensorFlow.