Computational Chemist - Liquid & Molecular Systems -- @Entalpic
Paris, France
Breega
Breega propels pioneering and purpose-driven founders from idea into impact. Crafted for founders by founders, we built Breega to provide start-ups with the help we wish we'd had.Our company: Entalpic
We are a dedicated team at the forefront of AI and chemistry, working to accelerate the energy transition. Our focus is on discovering new chemicals and materials that can lead to more sustainable practices in sectors where the need for change is most urgent. Specifically, we are developing a modern generative AI platform to discover new catalysts that optimize chemical reactions, significantly reducing CO2 emissions and thus making a substantial impact on the environment.
As an early-stage AI-driven startup backed by substantial funding (>8 million €), we base our approach on state-of-the-art academic research to drive practical business solutions. We value clear communication and simplicity in our approaches, promoting a constant optimization mindset.
Join Entalpic to be part of a growing team, eager to learn and adapt, united by the belief that our technology can make a significant positive impact and contribute to transforming carbon-intensive industries for a sustainable future.
Co-founders: Mathieu Galtier, Victor Schmidt, Alexandre Duval
Reporting & Job Location
You will report to the Chief Science Officer (CSO) of Entalpic and will be located in our Paris offices, with up to 2 days of remote work per week.
Mission Highlights
We are seeking a Computational Chemist to lead machine learning (ML)-driven material discovery for liquid-phase chemical systems, focusing on redox-active molecules, electrolytes, and molecule-solvent interactions. You will work at the interface of ML, computational chemistry, and experimental validation, ensuring AI-generated candidates are both theoretically sound and experimentally viable.
Your role will involve collaborating with the engineering & science team (~15 people) to enhance molecular generative models, optimize active learning workflows, integrate ML-based predictive proxies, and conduct DFT validation. Additionally, you will also work alongside experimental partners and industry clients to ensure that our computational discoveries translate into synthesizable and testable molecules, bridging the gap between AI-driven design and real-world applications.
Role & responsibilities
This position directly supports the company’s mission of discovering materials to optimize carbon intensive industries. You will be responsible for:
- Domain expertise – Identifying and prioritizing molecular and liquid-phase chemical systems where AI-driven discovery can accelerate innovation. This includes designing molecular compounds with optimized redox stability, ionic conductivity, and solubility for various applications.
- ML-driven molecular discovery – Collaborating with AI teams to extend generative models (GFlowNet, diffusion, flow-matching) to molecular and liquid-phase chemistry, incorporating reaction conditions, functional group modifications, and solubility constraints.
- Computational modeling & validation – Running DFT, MD, or cheminformatics tools to validate AI-generated molecules.
- Collaboration with experimentalists – Engaging with wet-lab researchers to ensure AI-driven discoveries are synthesizable and testable, iterating based on real-world feedback. The ideal candidate will be comfortable discussing and assisting in the design of synthetic procedures for target molecules.
- Scientific communication – Contributing to research publications, patents, and internal reports to ensure knowledge transfer and impact.
Profile
- PhD in Computational Chemistry, Material Science, or related field.
- Expertise in quantum chemistry (DFT, semi-empirical methods, MD simulations).
- Solid background in machine learning interatomic potentials (i.e. graph neural networks) and/or generative models for molecular compounds.
- Ability to work with experimentalists and integrate synthesis constraints into computational workflows.
- Proficiency in Python, Git, Cheminformatics (RDKit, ASE), simulation packages (Psi4, LAMMPS) and ML frameworks (PyTorch, JAX).
- Ability to integrate computational and experimental constraints into molecule design.
- Strong analytical skills, problem-solving ability, and motivation to work in a fast-paced startup environment.
- Excellent communication skills in English and ability to disseminate science to others.
Bonus Skills
- Hands-on expertise in high-throughput screening or automation in computational chemistry.
- Experience with wet lab liquid phase chemistry, either through research or teaching positions (e.g. teaching an organic chemistry lab course).
- Experience with electrochemical systems (e.g., electrolytes, batteries, fuel cells).
- Industry experience in battery R&D, computational materials science, or molecular design.
Compensation & benefits
We are a no-nonsense startup, where we favor a sustainable culture promoting work-life balance and good compensation over football tables and free food. We offer:
- A competitive salary
- Equity (BSPCE), to reflect the value you bring to Entalpic and to foster a shared journey
- Comprehensive health insurance (Alan blue)
- French level paid leave and time-off work
- Dynamic work setting. Although our preference is for in-person collaboration, we will be flexible with occasional remote work arrangements.
- A relocation package and thorough visa support.
- and more to come as we grow
Entalpic is dedicated to equal opportunity employment and fosters an environment that is open and respectful of diversity. All applicants are encouraged to apply, even if you don’t meet all above requirements. If you have passion for our mission and believe you can contribute, we want to hear from you.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Chemistry Engineering Generative AI Generative modeling Git JAX Machine Learning PhD Python PyTorch R R&D RDKit Research Teaching
Perks/benefits: Career development Competitive pay Equity / stock options Flex hours Flex vacation Health care Relocation support Salary bonus Startup environment
More jobs like this
Explore more career opportunities
Find even more open roles below ordered by popularity of job title or skills/products/technologies used.