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 develop 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 (>5m), 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.

Mission Highlights

As a Material Scientist, you will play an instrumental role in designing physics-informed machine learning models aimed to accelerate materials discovery. You will lead the integration of physicochemical & manufacturing constraints into our genAI pipeline for various applications of interest. This role does not involve performing direct lab experiments but a close collaboration with our research and engineering teams (~10 people) to enhance the performance, scalability and impact of our AI-driven solutions, while also engaging with clients to meet their needs and deliver superior materials. 

Role & responsibilities

This position directly supports the company’s mission of discovering materials to optimize carbon intensive industries. You will be responsible for:

• Application domain exploration: identify new application domains where our generative AI platform can have great impact. 
• Literature review: stay abreast of state-of-the-art methods and discoveries in AI-driven for material discovery.
• ML models: collaborate with ML teams to integrate relevant physicochemical and manufacturing constraints within our generative ML algorithms. 
• Active learning: contribute domain expertise to active learning strategies, enhancing sample selection and model generalization.
• Candidates evaluation: evaluate the potential of the catalyst candidates generated by our platform, creating meaningful metrics that meet project goals.
• Communication & Leadership: transmit application requirements to ML teams, guide catalyst experiments and present findings to the material science community & stakeholders.
• Collaborative development: Work closely with interdisciplinary teams to deliver innovative material candidates for specific applications.

Profile

• PhD in Chemistry, Chemical Engineering, Material Science or a closely related field, with a focus on catalysis.
• 3+ years of post-PhD experience in materials discovery, with proven R&D in heterogeneous catalyst design, synthesis, characterization and evaluation. 
• Familiarity with machine learning methods and convinced of their potential to revolutionize materials discovery.
• Excellent communication skills in English.
• Proven ability to work with interdisciplinary teams.
• Strong analytical skills and problem solving ability.
• Thrives in a fast-paced, evolving startup environment.

Bonuses

• Publications in several international peer-reviewed journals or conferences.
• Experience with computational modeling for catalyst design and optimization, particularly in running DFT simulations.

Expertise

• Material Science: general knowledge of broad chemistry and physics. 
• Chemical reactions & catalysis: strong theoretical and practical knowledge of heterogeneous catalysis principles, understanding of reaction mechanisms and their description through transition state theory. 
• Material synthesis: experience with catalysts synthesis, characterisation and evaluation. 
• Machine Learning: basic understanding of ML theories and practices, especially related to predictive & generative methods for 3D atomic systems.
• Programming: some knowledge of Python programming and Git version control.

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.
• 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.