About this role
About the RoleWe 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 DoDefine 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 ForRequired:
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 & BenefitsCompensation 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.
LocationThis 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.