A well-funded, seed-stage deeptech startup operating at the intersection of physics-informed AI, robotics, and materials science is looking for a Head of AI Research to define and lead its AI-for-Materials research agenda. Based in Berlin, Germany, this is a founding-level research leadership role with real scientific autonomy and direct influence over the company's long-term direction.
The company runs a fully autonomous experimental laboratory that integrates generative AI with robotic experimentation to dramatically accelerate materials discovery — particularly for clean energy and electrocatalysis applications. The Head of AI Research will shape the core scientific engine behind this platform: inventing new representations, learning paradigms, and evaluation frameworks that connect experiments, simulations, and models into reliable end-to-end discovery pipelines.
This role sits at the boundary of machine learning, physics, chemistry, and automated experimentation. It is suited to someone who thinks deeply about where existing ML paradigms fall short for physical matter — and who has the scientific taste and leadership experience to build what must come next.
Visa sponsorship is not available. Candidates must be eligible to work in Germany without employer sponsorship.
Set the research thesis for AI-native materials discovery; define high-impact research bets and prioritize ruthlessly.
Identify where existing ML paradigms fail for physical systems and specify what must be built instead.
Lead development of a Materials World Model that integrates experimental data, simulations, and learned representations.
Collaborate cross-functionally with Programs, Hardware & Automation, and Software Architecture teams to embed research into full discovery loops.
Ensure models remain grounded in physical reality and experimental feedback — not abstract data alone.
Balance long-horizon research ambitions with near-term deliverables and milestones.
Build and lead a world-class research team: hire, mentor, and challenge senior ML researchers and scientists.
Foster a culture of deep thinking, honest evaluation, scientific taste, and intellectual courage.
Shape the broader field through external collaborations and a clear, opinionated point of view on future directions.
Required
PhD in machine learning, physics, chemistry, or a closely related field (or equivalent research experience demonstrating the same depth).
7+ years of machine learning research experience, including demonstrated leadership of senior individual contributors or a research team.
Deep expertise in physics-informed machine learning and representation learning for materials, molecules, or closely related physical domains.
Hands-on experience building end-to-end discovery pipelines that combine experiments, simulations, and learned models.
Proven track record of setting a research agenda — defining a thesis, identifying high-leverage bets, and driving them to completion.
Ability to recruit, mentor, and develop a multi-disciplinary research team with rigorous scientific evaluation standards.
Strong cross-disciplinary communication skills; comfortable influencing stakeholders, collaborators, and external partners.
Eligibility to work in Berlin, Germany without employer visa sponsorship.
Fluency in English; additional languages are a plus.
Nice to Have
Background or strong intuition for electrochemistry, catalysis, or energy materials.
Experience with foundation models or multi-modal scientific ML.
Prior experience operating in an early-stage startup or research-intensive deeptech environment.
This is an on-site / hybrid role based in Berlin, Germany. The team works together in Berlin; remote-only arrangements are not available for this position. Visa sponsorship is not offered.
Define research direction at a company tackling one of the hardest and most consequential problems in science — materials discovery for the net-zero transition.
Work at the frontier of physics-informed AI, autonomous experimentation, and large-scale scientific data generation.
Build and lead a senior research team from an early stage, with significant influence over culture, hiring, and scientific standards.
Collaborate with a deeply technical, multi-disciplinary team backed by leading European and international deeptech investors.
