About the Role

We are a seed-stage deeptech startup building an advanced materials acceleration platform that combines physics-informed AI, robotics, and real-world experimental data to dramatically shorten the timeline for discovering new materials — particularly for the energy sector. We are seeking a Head of AI Research to define and lead our AI-for-Materials research agenda.

This is a senior leadership role sitting at the intersection of machine learning, physics, chemistry, and automated experimentation. You will shape the scientific vision that translates cutting-edge research insight into reliable, end-to-end discovery pipelines — and build the world-class team to execute it.

Location: Berlin, Germany (on-site). Visa sponsorship is not available — candidates must be eligible to work in Germany without employer sponsorship.

What You'll Do

• Define and champion the research thesis for AI-native materials discovery; set high-impact research bets and long-horizon strategy.

• Identify where existing ML paradigms fall short for physical matter and specify what needs to be invented instead.

• Lead development of a Materials World Model that bridges experiments, simulations, and learned representations.

• Collaborate closely with Programs, Hardware & Automation, and Software Architecture teams to embed research into end-to-end autonomous discovery loops.

• Ensure models stay grounded in physical reality and experimental feedback — not just abstract data.

• Balance ambitious long-horizon research goals with near-term deliverables and milestones.

• Build, hire, mentor, and challenge a multi-disciplinary team of senior ML researchers and scientists.

• Foster a culture of deep thinking, honest evaluation, scientific taste, and intellectual courage.

• Influence the broader scientific community through collaborations and a clear, opinionated point of view on future directions.

What We're Looking For

Required:

• Advanced degree (PhD strongly preferred) in machine learning, physics, chemistry, or a closely related field.

• 7+ years of machine learning research experience, including demonstrated leadership of senior individual contributors or head-of-team responsibility.

• Deep expertise in physics-informed machine learning, representation learning, or foundation models applied to materials science or related physical domains.

• Proven ability to build end-to-end discovery pipelines that integrate experiments, simulations, and models.

• Track record of setting and influencing a research agenda — defining thesis, prioritizing under uncertainty, and making irreversible bets.

• Strong intuition for physical systems, chemistry, and their constraints.

• Excellent cross-disciplinary communication skills; ability to influence technical and non-technical stakeholders and external collaborators.

• Fluency in English; additional languages are a plus.

• Eligibility to work in Germany without employer visa sponsorship.

Nice to Have:

• Background in scientific ML areas such as equivariant neural networks, generative models for molecules/materials, or multi-fidelity modeling.

• Experience in automated or autonomous laboratory environments.

• Familiarity with the energy materials landscape (e.g., batteries, catalysts, photovoltaics).

• Prior experience at a research institution, national laboratory, or deeptech startup.

Compensation & Benefits

Compensation details are not publicly listed for this role. A competitive package commensurate with the seniority and strategic importance of this position will be discussed during the interview process.

Location

This is a full-time, on-site role based in Berlin, Germany. Candidates must be willing and eligible to work in Berlin without employer-sponsored visa support.