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Discovery Scientists - AI for Science - Paris
Description
We are building a team of exceptional Discovery Scientists, who can identify and solve key problems in their respective fields, here in STEM, with a particular focus on Physics, Chemistry, and Material science. The idea is to leverage the cutting-edge capabilities in AI of our Core Science organization. You will be able to shape the mission and:
- Accelerate scientific discovery through high quality, open access research
- Be empowered with advanced AI tools, participate to improving these tools in STEM, and the freedom to explore high-impact projects at the intersection of your domain and AI.
- Participate in the growth of fundamental and industrial applications in AI for science
Generally, our team will focus on two axis: (1) improving the models’ capabilities in solving open science problems and (2) systematically accelerating simulations.
- Identify and Define Impactful Problems: Proactively identify critical challenges in your field where AI/ML can drive breakthroughs.
• End-to-End Research Ownership: Lead independent research projects from ideation to implementation, including literature review, hypothesis formulation, numerical experimentation, and validation.
• Develop and Apply AI/ML Solutions: Design, implement, and refine advanced algorithms, models, and frameworks (e.g., deep learning, LLMs, agentic AI) to address domain-specific problems.
• Collaborate and Innovate: Work with a multidisciplinary team of scientists, engineers, and domain experts (including customers) to push the boundaries of what’s possible with AI in science.
• Autonomy and Initiative: Operate with high autonomy, setting your own research agenda and driving projects to completion with minimal oversight.
Qualifications
- Domain Expertise: Strong understanding and research capabilities in at least one scientific domain (e.g., physics, chemistry or materials science), demonstrated by first-author publications, open-source contributions, or other impactful projects.
• Track record in AI/ML; the ability to shed light on hard, real-life problems with an AI solution, demonstrated by further contributions.
• Broad experience in coding, for scientific computing and in machine learning, deep learning, and/or large language models.
• Hands-on experience using frameworks like PyTorch or TensorFlow is especially appreciated.
• Interdisciplinarity: ability to communicate to a broad-non specialized audience while still remaining technical.
• Customer Collaboration Experience: Experience working with customers or end-users to refine requirements is also appreciated.
• Low ego and team spirit mindset
• Embraces hands-on, operational work
• Domain Expertise: Strong understanding and research capabilities in at least one scientific domain (e.g., physics, chemistry or materials science), demonstrated by first-author publications, open-source contributions, or other impactful projects.
• Track record in AI/ML; the ability to shed light on hard, real-life problems with an AI solution, demonstrated by further contributions.
• Broad experience in coding, for scientific computing and in machine learning, deep learning, and/or large language models.
• Hands-on experience using frameworks like PyTorch or TensorFlow is especially appreciated.
• Interdisciplinarity: ability to communicate to a broad-non specialized audience while still remaining technical.
• Customer Collaboration Experience: Experience working with customers or end-users to refine requirements is also appreciated.
• Low ego and team spirit mindset
• Embraces hands-on, operational work
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