Job Opportunities API

Dunia Innovations is seeking a Head of AI Research to define and lead its AI-for-Materials agenda, advancing the science of materials discovery by inventing new representations, learning paradigms, and evaluation frameworks. This role sits at the intersection of machine learning, physics, chemistry, and automated experimentation, shaping systems that translate scientific insight into reliable discovery pipelines. What you'll do • Define how AI can understand, reason about, and discover materials across scales. • Set Dunia’s research thesis for AI-native materials discovery and decide high-impact research bets. • Identify where existing ML paradigms fail for physical matter and specify what must be built instead. • Spearhead development of Dunia's Materials World Model to connect experiments, simulations, and models. • Work with Programs, Hardware & Automation, and Software Architecture to embed research into end-to-end discovery loops. • Ensure models remain grounded in physical reality and experimental feedback rather than abstract data alone. • Balance long-horizon research goals with near-term deliverables while maintaining ambition. • Build and lead a world-class research team, hiring, mentoring, and challenging senior ML researchers and scientists. • Create a culture that values deep thinking, honest evaluation, scientific taste, and intellectual courage. • Influence the broader field through collaborations and a clear, opinionated point of view on future directions. What Dunia Innovations is looking for • Advanced degree in machine learning or related fields, with a PhD preferred and strong scientific fundamentals. • 7+ years of experience in AI research, including leadership of senior individual contributors. • Deep experience in representation learning, scientific ML, or foundation models relevant to materials science. • Background or strong intuition for physical systems, chemistry, or physics and their constraints. • Proven ability to operate at the boundary between theory, systems, and real-world experimental feedback. • Demonstrated scientific judgment, comfort with irreversible prioritization under uncertainty, and clear communication skills. • English fluency; additional languages are a plus.