Entalpic Research Fellowship

About The Program Entalpic Research Fellowship is a selective initiative designed to empower exceptional PhD students & post‑doc working at the intersection of Artificial Intelligence and Materials Science. Participants join a vibrant community of scientists advancing fundamental and applied research in catalysis, energy storage, sustainability, and material discovery. They benefit from financial support, deep scientific mentorship and hands‑on collaboration—all while maintaining their academic affiliations. This program commits to supporting open research with real‑world impact. Key Facts Program Duration: 12+ months Track 1: Research Project Track 2: Research project & 4–6 month Internship Start Dates: Cohort 1: Apply by October 24, 2025 → Decisions in November → Start in January 2026 Cohort 2: Apply by February 28, 2026 → Decisions in March → Start in May/June 2026 About Entalpic Entalpic is a young startup building the next generation of AI‑powered tools for chemistry and materials discovery. Our work combines machine learning, scientific computing, and experimental validation to accelerate innovation in catalysis, battery materials, coating and sustainable industrial processes. Backed by leading VCs, we have assembled a diverse team of scientists and engineers from top institutions like Berkeley, Google, Mila, Polytechnique, Stanford, Intel and Meta. Based in Paris, we foster a vibrant and collaborative atmosphere, transforming materials R&D to power a sustainable future. What You’ll Work On As an Entalpic Research Fellow, you will pursue your own PhD (or postdoc) research at your current university while engaging with Entalpic’s scientific ecosystem. Research projects are therefore expected to remain open‑source and academic in nature, but they should be aligned with Entalpic’s strategic goals & challenges, i.e. inspired by real industrial and environmental challenges. In this program, they should contribute to and be released on LeMaterial. Main Focus Dataset creation, curation, and data‑centric modelling (quantum or experimental data) Potential Focus Areas (but not limited to) Generative design of new materials, molecules, and surfaces Predictive models for properties, synthesis, and performance Multiscale modeling approaches (atomic → meso → macro) Uncertainty quantification and active learning Agentic science for autonomous discovery workflows Program Benefits Financial Support: receive a top‑up sponsorship of 10–15k€, independent from any internship salary. This grant is flexible and can be used for travel, research expenses, conference participation, or living support. Scientific Mentorship: work closely with an Entalpic mentor for feedback, co‑ideation, and scientific dialogue. Monthly check‑ins, joint reading groups, and invitations to internal workshops create an ongoing collaboration. Real‑World Engagement: work side‑by‑side with Entalpic’s team on a strategic research direction. For the internship track, complete a 4–6 month paid internship in Paris, tailored to the candidate’s background and interests, potentially involving core in‑house R&D projects. Community & Visibility: join a small cohort of peers, present your work at internal and external events, and gain visibility through Entalpic’s network of partners and collaborators. Earn recognition as an “Entalpic Research Fellow 2026”. Career Opportunities: upon completion of the PhD, top‑performing participants may be offered a full‑time research or engineering position at Entalpic. Who Should Apply Be enrolled in a PhD program in machine learning, computational chemistry, materials science, or related fields. Commit to a clear deliverable (dataset, model, method, code, etc.) to be released on LeMaterial before the end of the program. Have publications, open‑source contributions, or prior work in AI for science. (For the internship track) Be willing to complete a 4–6 month internship at Entalpic — starting in January or May/June. Bonus Qualifications (not required but appreciated) Fluent in Python and experience with deep learning models & frameworks (e.g., PyTorch) Experience working with quantum simulations, large datasets, or scientific models Prior work on ML applications to scientific domains (e.g., crystals, catalysis, batteries…) We strongly encourage applications from candidates of all backgrounds, and are especially supportive of those from underrepresented groups in science and technology. How to Apply? Please include: CV — with links to relevant projects, publications or code Research proposal — up to 2 pages, no strict format, with unlimited references, outlining your current research, its impact, and alignment with Entalpic’s vision. (Optional) Letter of recommendation — preferably from your PhD advisor Specify which track you apply to: Track 1 (no internship) or Track 2 (with internship). Questions? Email us at research-fellowship@entalpic.ai. We’re happy to clarify the program or review your eligibility in advance. Seniority level Internship Employment type Internship Job function Research, Analyst, and Information Technology Industries Venture Capital and Private Equity Principals #J-18808-Ljbffr