Research Scientist, Material Intelligence

<h2>Snapshot</h2> <p><span style="font-weight: 400;">Science is at the heart of everything we do at Google DeepMind. From the beginning, we took inspiration from science to build better algorithms, and now, we want to use our toolkit to accelerate scientific discovery. By bringing together specialists with backgrounds in machine learning, computer science, physics, chemistry, biology and more, we’re optimistic that we can build new methods that will push the boundaries of what is possible and help solve the biggest problems facing humanity.</span></p> <h2>About Us</h2> <p>Google DeepMind (GDM) is pursuing a ground-breaking research program in materials, aiming to accelerate the discovery of new functional materials by combining the predictive power of artificial intelligence (AI) and computational simulation with automated experimentation. The team is establishing experimental capacity to create a closed-loop, AI-driven discovery engine. Computational simulation is critical for grounding the AI and providing quick <em>in silico</em> feedback before materials are sent off to the lab for experimental validation.</p> <h2>The Role</h2> <p>We are seeking an exceptional and highly motivated expert in computational materials science, with broad expertise simulating diverse material classes, to help drive our in-silico discovery efforts. This is a senior position with a unique role blending scientific leadership, hands-on modeling, strategic input, and mentorship. You will be instrumental in guiding the computational team, supervising junior researchers, and refining the critical in-silico feedback loop that is at the heart of our mission.</p> <h3>Key responsibilities:</h3> <ul> <li>Computational Leadership &amp; Supervision: Lead and mentor a team of computational materials scientists, guiding project roadmaps, fostering scientific growth, and ensuring high-quality research output.</li> <li>Modeling Strategy &amp; Execution: Design and execute large-scale computational scr