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# Application Lead (Vapor Pressure Precursor Chemistry) - @Entalpic

- **Company:** Breega
- **Location:** Paris, France (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Computer Simulation, Computer Programming, Databases, Digital Data, Experimental Data, Python (Programming Language), Strategies of Testing, Data Processing, Large Language Models, AI Platforms, Information Technology
- **Published:** September 25, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=3971ccb020e3b09d

## About the Role

* PhD in chemistry, materials chemistry, chemical engineering, or a related field (not required if your experience is strong).
 * Several years of experience in vapor deposition precursor chemistry : molecular, organometallic, or coordination chemistry for thin-film deposition (ALD/CVD/PVC or a closely adjacent field); with a hands-on experimental or synthetic background at some point in your career.
 * Familiarity with software programming (e.g. python) for analysis of chemistry/materials science characterization data. At least, a strong willingness to learn it.
 * An organised, structured and data-minded approach: able to deal with many projects, define data processing conventions and spot subtleties in experimental datasets that others miss.
 * Ability to communicate outside of the experimental chemistry culture, translating experimental chemistry values and constraints to other team members (eg with a computer science background). Excellent communication skills in English, and comfort in client-, partner-, and conference-facing settings.
 * Ability to operate independently and drive projects in a fast-paced startup environment.

Bonus Skills:

 * Exposure to LLMs, agents, data/informatics tooling, electronic lab notebooks, databases, etc
 * An existing network across the precursor-supplier, equipment providers, fabs and research institutes.

## Description

As Applications Lead (Vapor Deposition Precursor Chemistry) at Entalpic, your mission will be to make our AI platform truly useful for real-world precursor discovery and atomic-scale manufacturing. You will be our experimental domain authority on precursors, connecting molecular design, deposition performance and film properties with our computational models.

You will help build the experimental backbone needed to turn AI predictions into validated discoveries: shaping our precursor development and testing strategy, developing a strong network of labs and industrial collaborators, working with software engineers to ensure that experimental data captures the chemistry and process subtleties that matter in practice.

Ultimately, you will help create a tight learning loop where AI models guide which experiments to pursue and use results to steer the next iteration - bringing this expertise into client projects, partnerships, and the broader semiconductor ecosystem., This position directly supports the company's mission of accelerating the discovery of new materials and manufacturing processes. You will be responsible for:

 * Partnerships: own the relationships with our network of external experimental labs and industrial partners, coordinate experimental campaigns, and make sure we get high quality experimental data in a timely fashion.
 * Improve quality and homogeneity of internal datasets by (a) defining gold standard protocols for experimental data generation, (b) harmonising digital data incoming from various sources, often programmatically, and feed observations to technical teams (c) hire, coordinate and animate our network of PhD collaborators for data curation
 * Being our precursor chemistry domain authority: bring deep, practical command of ligand and precursor families, volatility and thermal stability, reactivity with surface, and how precursor choice maps onto film properties - including the know-how that doesn't make it into papers.
 * Contribute to our experimental strategy: help define which chemistries and precursor families to explore, screen, prioritize.
 * Growth: support client delivery, bring domain knowledge into our product development, contribute to partnerships conversations and represent Entalpic at conference when needed.

This role is NOT about doing experiments in a lab. It can lean either towards partnerships or towards technical work on data quality & AI platform improvement, depending on your strengths., * Interview with the hiring manager

 * Technical interview on your precursor chemistry and process expertise
 * Case discussion on a real Entalpic problem (data quality / experimental strategy)
 * Final interview with the CSO