Computational Chemistry Intern (Materials Modeling / Molecular Simulation)

About Us

SES AI is a leader in AI-driven materials discovery, building the Molecular Universe (MU) platform to accelerate the development of next-generation battery chemistries. Our work integrates physics-based simulations, machine learning, and large-scale data infrastructure to enable rapid innovation in material science with a dedication to AI for Science.

To learn more about SES, please visit: www.ses.ai

Position Scope

SES AI is seeking a Computational Chemistry Interns to join the Molecular Universe team and support computational modeling and simulation of advanced electrolyte systems. This is a hands-on research role focused on liquid-phase molecular dynamics (MD) simulations, especially for electrolyte systems relevant to next-generation batteries.

Interns will receive training and mentorship from our computational scientist, and collaborate across global teams.

• Location: China (Remote)
• Duration: 6 months

Responsibilities

• Contribute to the SES Molecular Universe project by supporting computational chemistry modeling and simulation of advanced electrolyte systems
• Independently or collaboratively perform molecular dynamics simulations for liquid-phase systems, especially electrolytes, including system construction, initial structure generation, and simulation parameter setup
• Execute the full MD workflow, including job submission, HPC resource utilization, run monitoring, troubleshooting, and issue resolution
• Analyze simulation results in depth, including but not limited to:
• Structural properties such as radial distribution functions (RDF), coordination numbers, and solvation structures
• Dynamic properties such as diffusion coefficients and ion transport behavior
• Thermodynamic and statistical property extraction
• Build and improve automated data-processing pipelines to enhance simulation efficiency, reproducibility, and scalability
• Convert simulation outputs into clear reports, visualizations, and presentations that support scientific and engineering decision-making
• Collaborate with internal teams to improve workflow robustness and reproducibility across simulation pipelines
• Support the scaling and engineering of molecular simulation workflows within the MU platform

Preferred / Advanced Responsibilities

• Contribute to force field development, optimization, and validation for electrolyte or ion-containing systems
• Explore higher-accuracy or higher-efficiency simulation methodologies
• Participate in the engineering and platformization of simulation workflows, including workflow automation, orchestration, and task scheduling

Qualifications

• PhD (or PhD candidate) in Computational Chemistry, Materials Science, Chemical Engineering, Physical Chemistry, or a related field
• Hands-on experience with molecular dynamics simulations, particularly for liquid-phase systems
• Familiarity with common simulation tools such as GROMACS, LAMMPS, OPENMM, or similar packages
• Experience with electrolyte systems, ionic systems, battery-related simulations, or sodium-ion systems is strongly preferred
• Understanding of molecular force fields, including basic principles of force field development and parameterization; direct experience is preferred
• Programming skills in Python or similar languages for data analysis, workflow automation, and simulation pipeline development
• Strong problem-solving skills and the ability to diagnose simulation instability, convergence issues, and physical inconsistencies
• Excellent communication skills, with the ability to clearly present technical findings to both technical and non-technical audiences
• Ability to work effectively in a collaborative, international research environment

Language Requirement

• Professional English proficiency is required
• For positions based in Korea, Japan, and Mainland China, candidates must speak English fluently and be able to conduct professional work in English, including technical discussions, documentation, and presentations

Why Join SES AI

• Work on real, high-impact problems in next-generation battery materials discovery
• Contribute to production-relevant simulation workflows rather than isolated academic projects
• Gain exposure to the intersection of molecular simulation, automation, AI for Science, and materials innovation
• Collaborate with a global team across simulation, machine learning, and experimental validation

Computational Chemistry Intern (Materials Modeling / Molecular Simulation)

About Us

SES AI is a leader in AI-driven materials discovery, building the Molecular Universe (MU) platform to accelerate the development of next-generation battery chemistries. Our work integrates physics-based simulations, machine learning, and large-scale data infrastructure to enable rapid innovation in material science with a dedication to AI for Science.

To learn more about SES, please visit: www.ses.ai

Position Scope

SES AI is seeking a Computational Chemistry Interns to join the Molecular Universe team and support computational modeling and simulation of advanced electrolyte systems. This is a hands-on research role focused on liquid-phase molecular dynamics (MD) simulations, especially for electrolyte systems relevant to next-generation batteries.

Interns will receive training and mentorship from our computational scientist, and collaborate across global teams.

• Location: South Korea (Remote)
• Duration: 6 months

Responsibilities

• Contribute to the SES Molecular Universe project by supporting computational chemistry modeling and simulation of advanced electrolyte systems
• Independently or collaboratively perform molecular dynamics simulations for liquid-phase systems, especially electrolytes, including system construction, initial structure generation, and simulation parameter setup
• Execute the full MD workflow, including job submission, HPC resource utilization, run monitoring, troubleshooting, and issue resolution
• Analyze simulation results in depth, including but not limited to:
• Structural properties such as radial distribution functions (RDF), coordination numbers, and solvation structures
• Dynamic properties such as diffusion coefficients and ion transport behavior
• Thermodynamic and statistical property extraction
• Build and improve automated data-processing pipelines to enhance simulation efficiency, reproducibility, and scalability
• Convert simulation outputs into clear reports, visualizations, and presentations that support scientific and engineering decision-making
• Collaborate with internal teams to improve workflow robustness and reproducibility across simulation pipelines
• Support the scaling and engineering of molecular simulation workflows within the MU platform

Preferred / Advanced Responsibilities

• Contribute to force field development, optimization, and validation for electrolyte or ion-containing systems
• Explore higher-accuracy or higher-efficiency simulation methodologies
• Participate in the engineering and platformization of simulation workflows, including workflow automation, orchestration, and task scheduling

Qualifications

• PhD (or PhD candidate) in Computational Chemistry, Materials Science, Chemical Engineering, Physical Chemistry, or a related field
• Hands-on experience with molecular dynamics simulations, particularly for liquid-phase systems
• Familiarity with common simulation tools such as GROMACS, LAMMPS, OPENMM, or similar packages
• Experience with electrolyte systems, ionic systems, battery-related simulations, or sodium-ion systems is strongly preferred
• Understanding of molecular force fields, including basic principles of force field development and parameterization; direct experience is preferred
• Programming skills in Python or similar languages for data analysis, workflow automation, and simulation pipeline development
• Strong problem-solving skills and the ability to diagnose simulation instability, convergence issues, and physical inconsistencies
• Excellent communication skills, with the ability to clearly present technical findings to both technical and non-technical audiences
• Ability to work effectively in a collaborative, international research environment

Language Requirement

• Professional English proficiency is required
• For positions based in Korea, Japan, and Mainland China, candidates must speak English fluently and be able to conduct professional work in English, including technical discussions, documentation, and presentations

Why Join SES AI

• Work on real, high-impact problems in next-generation battery materials discovery
• Contribute to production-relevant simulation workflows rather than isolated academic projects
• Gain exposure to the intersection of molecular simulation, automation, AI for Science, and materials innovation
• Collaborate with a global team across simulation, machine learning, and experimental validation

Computational Chemistry Intern (Materials Modeling / Molecular Simulation)

About Us

SES AI is a leader in AI-driven materials discovery, building the Molecular Universe (MU) platform to accelerate the development of next-generation battery chemistries. Our work integrates physics-based simulations, machine learning, and large-scale data infrastructure to enable rapid innovation in material science with a dedication to AI for Science.

To learn more about SES, please visit: www.ses.ai

Position Scope

SES AI is seeking a Computational Chemistry Interns to join the Molecular Universe team and support computational modeling and simulation of advanced electrolyte systems. This is a hands-on research role focused on liquid-phase molecular dynamics (MD) simulations, especially for electrolyte systems relevant to next-generation batteries.

Interns will receive training and mentorship from our computational scientist, and collaborate across global teams.

• Location: Japan (Remote)
• Duration: 6 months

Responsibilities

• Contribute to the SES Molecular Universe project by supporting computational chemistry modeling and simulation of advanced electrolyte systems
• Independently or collaboratively perform molecular dynamics simulations for liquid-phase systems, especially electrolytes, including system construction, initial structure generation, and simulation parameter setup
• Execute the full MD workflow, including job submission, HPC resource utilization, run monitoring, troubleshooting, and issue resolution
• Analyze simulation results in depth, including but not limited to:
• Structural properties such as radial distribution functions (RDF), coordination numbers, and solvation structures
• Dynamic properties such as diffusion coefficients and ion transport behavior
• Thermodynamic and statistical property extraction
• Build and improve automated data-processing pipelines to enhance simulation efficiency, reproducibility, and scalability
• Convert simulation outputs into clear reports, visualizations, and presentations that support scientific and engineering decision-making
• Collaborate with internal teams to improve workflow robustness and reproducibility across simulation pipelines
• Support the scaling and engineering of molecular simulation workflows within the MU platform

Preferred / Advanced Responsibilities

• Contribute to force field development, optimization, and validation for electrolyte or ion-containing systems
• Explore higher-accuracy or higher-efficiency simulation methodologies
• Participate in the engineering and platformization of simulation workflows, including workflow automation, orchestration, and task scheduling

Qualifications

• PhD (or PhD candidate) in Computational Chemistry, Materials Science, Chemical Engineering, Physical Chemistry, or a related field
• Hands-on experience with molecular dynamics simulations, particularly for liquid-phase systems
• Familiarity with common simulation tools such as GROMACS, LAMMPS, OPENMM, or similar packages
• Experience with electrolyte systems, ionic systems, battery-related simulations, or sodium-ion systems is strongly preferred
• Understanding of molecular force fields, including basic principles of force field development and parameterization; direct experience is preferred
• Programming skills in Python or similar languages for data analysis, workflow automation, and simulation pipeline development
• Strong problem-solving skills and the ability to diagnose simulation instability, convergence issues, and physical inconsistencies
• Excellent communication skills, with the ability to clearly present technical findings to both technical and non-technical audiences
• Ability to work effectively in a collaborative, international research environment

Language Requirement

• Professional English proficiency is required
• For positions based in Korea, Japan, and Mainland China, candidates must speak English fluently and be able to conduct professional work in English, including technical discussions, documentation, and presentations

Why Join SES AI

• Work on real, high-impact problems in next-generation battery materials discovery
• Contribute to production-relevant simulation workflows rather than isolated academic projects
• Gain exposure to the intersection of molecular simulation, automation, AI for Science, and materials innovation
• Collaborate with a global team across simulation, machine learning, and experimental validation

SES AI Corp. (NYSE: SES) is dedicated to accelerating the world’s energy transition through groundbreaking material discovery and advanced battery management. We are at the forefront of revolutionizing battery creation, pioneering the integration of cutting-edge machine learning into our research and development. Our AI-enhanced, high-energy-density and high-power-density Li-Metal and Li-ion batteries are unique; they are the first in the world to utilize electrolyte materials discovered by AI. This powerful combination of "AI for science" and material engineering enables batteries that can be used across various applications, including transportation (land and air), energy storage, robotics, and drones. 

To learn more about us, please visit: www.ses.ai 

What We Offer: 

• A highly competitive salary and robust benefits package, including comprehensive health coverage and an attractive equity/stock options program within our NYSE-listed company. 

• The opportunity to contribute directly to a meaningful scientific project—accelerating the global energy transition—with a clear and broad public impact. 

• Work in a dynamic, collaborative, and innovative environment at the intersection of AI and material science, driving the next generation of battery technology. 

• Significant opportunities for professional growth and career development as you work alongside leading experts in AI, R&D, and engineering. 

• Access to state-of-the-art facilities and proprietary technologies are used to discover and deploy AI-enhanced battery solutions. 

What we Need: 

The SES AI Prometheus team is seeking an exceptional Commercial & Business Development Leader to drive B2B sales and partnership growth within the New Energy and AI4Science markets. This role requires deep technical domain understanding of battery materials, chemical engineering, and laboratory automation to effectively commercialize our AI-powered scientific solutions. As the Business Development Manager, you will be the commercial face of our advanced AI platforms, responsible for market penetration and client acquisition. 

Essential Duties and Responsibilities: 

• Sales & Market Strategy 

• Lead technical B2B sales efforts within the new energy, lithium battery, and chemical materials markets, managing the entire enterprise account lifecycle. 

• Identify and secure clients in frontier technology areas, specifically driving the adoption of AI-powered smart lab solutions. 

• Conduct comprehensive market analysis to identify key opportunities and strategic partnerships within the energy OEM market and chemical materials industry. 
   

• Client Engagement & Solution Delivery 

• Translate complex customer needs and technical challenges into clear solution requirements for the product and engineering teams. 

• Develop and deliver compelling technical solution presentations that articulate the unique value proposition of our AI solutions within material science workflows. 

• Manage the negotiation process, driving agreements to completion and securing commercial success. 
   

• Domain & Product Integration 

• Maintain a deep understanding of customer battery/chemical material workflows, effectively communicating the value of our AI4Science ecosystem, including laboratory automation. 
   

Education and/or Experience: 

• Education: B.A. or B.S. in Applied Chemistry, Chemical Engineering, Materials Science, or a closely related technical field. 

• Career Path: A career progression that began in a technical role (e.g., Chemical Engineer) and transitioned into a customer technical supporting sales or business development position. 

• Technical B2B Sales: Proven track record in technical B2B sales, negotiating and closing enterprise accounts in relevant markets (e.g., new energy, battery, chemical materials). 

• Domain Literacy: Deep technical literacy in battery materials, lithium battery technology, and the broader new energy ecosystem. 

Preferred Qualifications: 

• AI4Science Focus: Direct experience with the commercialization of AI4Science platforms, data-driven solutions, or smart lab automation systems. 

• Target Background: Previous experience at major battery manufacturers or suppliers (e.g., BYD, CALB, Wanhua) or at specialized smart-lab automation companies. 

• Frontier Tech Sales: Experience selling frontier tech solutions, demonstrating an ability to educate the market and secure early adopters. 

SES AI Corp. (NYSE: SES) is dedicated to accelerating the world’s energy transition through groundbreaking material discovery and advanced battery management. We are at the forefront of revolutionizing battery creation, pioneering the integration of cutting-edge machine learning into our research and development. Our AI-enhanced, high-energy-density and high-power-density Li-Metal and Li-ion batteries are unique; they are the first in the world to utilize electrolyte materials discovered by AI. This powerful combination of "AI for science" and material engineering enables batteries that can be used across various applications, including transportation (land and air), energy storage, robotics, and drones. 

To learn more about us, please visit: www.ses.ai 

Role Summary

The Business Development Representative (BDR) supports SES AI’s Business Development team across multiple business units by generating and qualifying inbound and outbound leads, coordinating conference and customer engagement activities, and supporting go-to-market programs in partnership with Marketing. This role is ideal for a motivated, curious, and highly organized individual who is eager to learn, communicates effectively, and uses automation and AI tools to maximize productivity.

Key Responsibilities

Lead Generation & Qualification

• Develop and execute outbound prospecting campaigns (email, phone, social) to create qualified pipeline.
• Respond to inbound inquiries and route opportunities to the appropriate Business Unit or Account Executive.
• Qualify leads using defined criteria (e.g., use case, technical fit, timeline, customer profile).
• Maintain accurate, timely CRM updates for contacts, accounts, activities, and next steps.

Automation & Enablement

• Set up and optimize automated prospecting sequences using sales automation and AI tools.
• Continuously test messaging, targeting, and cadence; recommend improvements based on performance data.
• Build and maintain scalable outreach playbooks in collaboration with Business Development and Marketing.

Conferences & Events

• Coordinate meeting schedules and outreach ahead of industry conferences and events.
• Represent SES AI at conferences; engage attendees to identify and qualify business opportunities.
• Perform timely post-event follow-up, ensuring prospects are entered into the CRM and routed appropriately.

Marketing & Content Support

• Support the development and distribution of marketing materials (one-pagers, decks, collateral for events).
• Drive registrations and attendance for marketing and educational events (webinars, workshops, briefings).
• Provide market and voice-of-customer feedback to inform messaging and positioning.

Success Measures (First 6–12 Months)

• Consistently meets or exceeds monthly targets for meetings set and qualified opportunities created.
• Improves outreach conversion rates through research, testing and analysis
• Maintains high-quality CRM hygiene (complete fields, accurate stages, clear next steps).
• Demonstrates strong follow-through and responsiveness with internal stakeholders and external prospects.
• Builds working knowledge of SES AI technologies and target customer applications.

Required Qualifications

• Bachelor’s degree in chemical engineering, Materials Science, Mechanical Engineering, Electrical Engineering, or a related field; or equivalent practical experience.
• Experience in a customer-facing role (sales, application engineering, customer success, technical support, field engineering, etc.).
• Strong written and verbal communication skills; comfortable engaging with technical and business audiences.
• Demonstrated ability to use productivity tools with attention to detail and follow-through.
• Proficiency in presentation building and PowerPoint, excel, and data analysis tools

Preferred Qualifications

• Prior sales or business development experience in a B2B environment.
• 1–2 years of experience in high-energy battery, energy storage, automotive, aviation, robotics, or adjacent deep-tech sectors.
• Hands-on experience with a CRM system (e.g., Apollo, Salesforce, HubSpot) and sales engagement tools.
• Familiarity with battery value chain, OEM/Tier 1 commercialization, or energy storage markets.
• Experience using AI-assisted tools for research, writing, outreach personalization, and workflow automation.

Working Conditions

• Travel: up to 20–30% (primarily conferences and customer meetings), as needed.
• This role is onsite. For exceptional candidates, we will consider a hybrid setup.

SES AI Corp. (NYSE: SES) is dedicated to accelerating the world’s energy transition through groundbreaking material discovery and advanced battery management. We are at the forefront of revolutionizing battery creation, pioneering the integration of cutting-edge machine learning into our research and development. Our AI-enhanced, high-energy-density and high-power-density Li-Metal and Li-ion batteries are unique; they are the first in the world to utilize electrolyte materials discovered by AI. This powerful combination of "AI for science" and material engineering enables batteries that can be used across various applications, including transportation (land and air), energy storage, robotics, and drones. 

 To learn more about us, please visit: www.ses.ai 

What We Offer: 

• A highly competitive salary and robust benefits package, including comprehensive health coverage and an attractive equity/stock options program within our NYSE-listed company. 

• The opportunity to contribute directly to a meaningful scientific project—accelerating the global energy transition—with a clear and broad public impact. 

• Work in a dynamic, collaborative, and innovative environment at the intersection of AI and material science, driving the next generation of battery technology. 

• Significant opportunities for professional growth and career development as you work alongside leading experts in AI, R&D, and engineering. 

• Access to state-of-the-art facilities and proprietary technologies are used to discover and deploy AI-enhanced battery solutions. 

What we Need: 

The SES AI Prometheus team is seeking an exceptional Computational Materials Scientist to combine physics-based simulation (DFT, MD, quantum modeling) with AI-assisted material prediction to generate high-quality training data and accelerate materials discovery. This role is crucial for advancing our understanding of electrochemical energy materials at the atomic level. As a Computational Materials Scientist, you will be a core data-driven modeler responsible for executing and automating complex simulations. 

Essential Duties and Responsibilities: 

• Atomistic Modeling & Simulation 

• Conduct and oversee DFT (Density Functional Theory), MD (Molecular Dynamics), and QM (Quantum Mechanics) simulations of battery components, including electrolytes, coatings, and electrodes. 

• Develop and refine ML-enhanced force fields and surrogate models to accelerate simulation time scales and enable multi-scale simulation efforts. 

• Apply expertise in atomistic simulation and quantum modeling to solve key challenges in electrochemical energy materials (e.g., batteries/fuel cells). 
   

• AI Data Generation & Prediction 

• Generate high-quality, structured simulation data to serve as training sets for AI property prediction models and material screening modules. 

• Contribute to the development of battery domain LLM features and advanced property-prediction models. 

• Automate complex simulation workflows using strong coding practices to enhance efficiency and scalability. 
   

• Collaboration & Tooling 

• Collaborate with experimental teams, leveraging a hybrid computational + experimental literacy to validate models and drive design iteration. 

• Utilize advanced simulation tools (VASP, Quantum Espresso) and data science libraries (TensorFlow, Pandas) to manage and analyze large datasets. 
   

Education and/or Experience: 

• Education: Ph.D. in Mechanical Engineering, Materials Science, Chemical Engineering, or a closely related computational/physics field. 

• Core Simulation Expertise: Deep and extensive experience in atomistic simulation and quantum modeling, including proficiency with key QM/DFT tools (VASP, Quantum Espresso) and MD simulations. 

• Domain Focus: Strong background in electrochemical energy materials and extensive computational work focused on batteries/fuel cells. 

• Coding Proficiency: Strong coding skills in Python (along with related libraries like Pandas and TensorFlow) for simulation workflow automation and data analysis. 

• ML Application: Experience in developing or utilizing ML-enhanced force fields and surrogate models for materials prediction., or equivalent practical experience. 

Preferred Qualifications: 

• LLM Development: Experience in developing battery domain LLM features or property-prediction models. 

• Hybrid Skillset: Demonstrated experience working in a hybrid computational + experimental environment. 

• Tooling Diversity: Familiarity with additional data analysis tools like R, SQL, MATLAB, and time-series forecasting libraries like Prophet. 

• Target Background: Previous experience at national laboratories, XtalPi, Entalpic, or deep battery modeling groups. 

SES AI Corp. (NYSE: SES) is dedicated to accelerating the world’s energy transition through groundbreaking material discovery and advanced battery management. We are at the forefront of revolutionizing battery creation, pioneering the integration of cutting-edge machine learning into our research and development. Our AI-enhanced, high-energy-density and high-power-density Li-Metal and Li-ion batteries are unique; they are the first in the world to utilize electrolyte materials discovered by AI. This powerful combination of "AI for science" and material engineering enables batteries that can be used across various applications, including transportation (land and air), energy storage, robotics, and drones. 

To learn more about us, please visit: www.ses.ai 

What We Offer: 

• A highly competitive salary and robust benefits package, including comprehensive health coverage and an attractive equity/stock options program within our NYSE-listed company. 

• The opportunity to contribute directly to a meaningful scientific project—accelerating the global energy transition—with a clear and broad public impact. 

• Work in a dynamic, collaborative, and innovative environment at the intersection of AI and material science, driving the next generation of battery technology. 

• Significant opportunities for professional growth and career development as you work alongside leading experts in AI, R&D, and engineering. 

• Access to state-of-the-art facilities and proprietary technologies are used to discover and deploy AI-enhanced battery solutions. 

What we Need: 

The SES AI Prometheus team is seeking an exceptional Technical Product Manager to serve as the product leader who translates complex scientific and AI research into actionable roadmap deliverables. This role requires deep literacy in computational materials science and AI4Science to coordinate strategy across our research, engineering, and materials teams. As the Technical Product Manager, you will be the driving force behind the product lifecycle for our AI-driven materials discovery platform. 

Essential Duties and Responsibilities: 

• Product Strategy & Roadmap Management 

• Define the product vision and manage the roadmap for our AI for materials software, ensuring alignment across the entire organization. 

• Translate complex scientific research and user needs into clear, customer-driven requirements for the engineering and research teams. 

• Oversee AI for materials software and research coordination, managing cross-functional deliverables and maintaining feature velocity. 
   

• Scientific & Research Alignment 

• Bridge scientific research and engineering by defining how scientific findings (e.g., from DFT/MD simulations) are integrated into a scalable and usable platform. 

• Identify opportunities for leveraging ML force-field models and AI molecular modeling to accelerate battery electrolyte design and performance. 

• Ensure platform usability and scaling by defining requirements that serve both the deep research community and material production teams. 
   

• Cross-Functional Leadership 

• Drive cross-functional alignment and execution across research (Computational Chemistry), core Engineering, and experimental Materials teams within a fast-paced AI and battery/materials organization. 
   

Education and/or Experience: 

• Education: Ph.D. in Computational Chemistry, Computational Materials Science, or a related quantitative field. Emphasis on Computational electrolyte design or interfacial chemistry is highly desirable. 

• Domain Literacy: Deep technical literacy in Computational Chemistry, including proficiency in DFT and MD simulations for materials analysis. 

• Product Management Experience: Proven experience as a Science-literate Product Manager overseeing the full software product lifecycle, specifically in the AI4Science or Materials Informatics space. 

• Cross-Functional Management: Demonstrated experience defining and managing complex roadmaps and coordinating across research, engineering, and materials organizations. 

• AI/ML Familiarity: Experience working with ML force-field models and other AI molecular modeling techniques. 
   

Preferred Qualifications: 

• Industry Experience: Previous experience in relevant high-tech organizations such as Cusp.ai, XtalPi, scientific computing startups, or established AI4Science product teams. 

• Broader Domain Application: Familiarity with computational tools and modeling related to other material science domains, such as aerospace thermal-barrier coatings or thermodynamics modeling in solar-cell materials. 

• Scaling Scientific Tools: A track record of successfully bridging scientific research outputs with platform usability and scaling in a production environment.