Materials Science Intern: ML for Structure-Process Relationships @Entalpic

Paris, France

Breega

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🚀 Mission Highlights

We are seeking a Materials Science Intern to lead machine learning (ML)-driven material discovery for catalytic reactions. This position will focus on developing an ML pipeline interfacing between theoretical and experimental materials science, specifically linking: 3D crystal structure --> synthesis procedure --> characterization data (XRD, XAS, TEM, etc) —> 3D structure. You will work at the interface of ML, computational chemistry, and experimental validation, ensuring of the chemical relevance of the data gathered and the ML models output.

Your role will involve collaborating with the engineering & science team (~20 people) to enhance Entalpic’s materials discovery pipeline, building models which connect simulated discoveries to the real world and providing experimental validation for Entalpic’s candidate materials. You will focus directly on interfacing open-source and AI-generated datasets of 3D structures with synthesis procedure development and characterization data. In so doing, you will work alongside experimental partners and industry clients to ensure that our computational discoveries have a viable path to experimental validation, 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 materials systems where AI-driven discovery can accelerate innovation. The ideal candidate will have the domain knowledge of materials science necessary to interface between computational chemists and experimental materials scientists.
  • Chemical literature parsing - Building LLM based pipelines to extract synthesis, characterization and performance values from the chemical/materials science literature. Combine domain knowledge in this space with a strong foundation in programming to be an active member of an LLM based extraction team.
  • ML models -- build models to predict material synthesizability, generate associated synthesis recipes, predict characterization data, and map synthesis procedure and characterization back to 3D structures.
  • 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 have experience with synthetic materials science/chemistry.
  • Scientific communication – Contributing to research publications, patents, and internal reports to ensure knowledge transfer and impact.

🤓 Expertise & skills

  • MSc and/or ****enrolled in a PhD in Chemistry, Chemical Engineering, Material Science, Machine Learning or a related field.
  • Proficiency with wet-lab materials science procedures.
  • Solid experience in building data & ML workflows in an experimental materials science/chemistry context
  • Proficiency in Python, Git, LLMs, and ML frameworks (PyTorch).
  • 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

  • Past experience working in a materials science lab (industry R&D is a big plus), especially in a synthetic materials science domain.

📅 Recruitment Process

  • Interview with the hiring manager
  • Technical interview about material science, catalysis and machine learning
  • Coding interview
  • Final interview with the C(cience)O

📍 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.

🏆 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:

  • Competitive salary
  • A dynamic and flexible work environment: Hybrid-Friendly with a minimum of 3 days in Paris offices per week (Station F)
  • 1 paid day off per month
  • Full reimbursement of your transport card
  • Professional development opportunities: access to conferences and internal learning sessions

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.

ℹ️ Information

  • Duration: 4-6 months
  • Start: From September 2025

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Tags: Chemistry Engineering Git LLMs Machine Learning ML models Open Source PhD Pipelines Python PyTorch R R&D Research

Perks/benefits: Career development Competitive pay Conferences Flex hours Salary bonus Startup environment

Region: Europe
Country: France

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