Using generative AI to simulate chemically disordered nuclear materials at the atomic level

Mathématiques, information  scientifique, logiciel Using generative AI to simulate chemically disordered nuclear materials at the atomic level H/F This postdoc aims to enhance PULSE, a generative (VAE) method revolutionizing predictions for disordered materials. You'll improve its accuracy, uncertainty quantification, and transition to a continuous latent space within a CEA consortium combining nuclear physics and AI. How do you predict a material's properties when the number of possible atomic configurations exceeds 2^2500? That is the bottleneck our IRESNE (nuclear fuel physics) and LIST (AI) teams have just cracked with PULSE, a generative (VAE) method published in Nature Scientific Reports, already cutting computational cost by more than two orders of magnitude (22,282 CPU hours down to 85 on a test case). With no known equivalent in the international literature, PULSE positions CEA as a pioneer in generative sampling of the configuration space of chemically disordered materials.This 24-month postdoc gives you the opportunity to drive this method toward its next generation, leading three ambitious, parallel research axes: pushing model accuracy on systems of several thousand atoms with an IWAE architecture; equipping it with the ability to quantify its own uncertainty — a prerequisite for any use in nuclear safety; and, in the second year, tackling a high-value exploratory axis — generalizing PULSE to a continuous latent space, opening the door to any disordered crystal or alloy.You will work at the heart of an all-CEA consortium bringing together two complementary strengths — atomistic nuclear fuel physics at IRESNE and state-of-the-art generative AI at LIST — with access to CEA supercomputers, the freedom to publish in top-tier journals, and the prospect of seeing your results feed directly into reactor safety analyses through the PLEIADES platform.A position built for a curious mind who wants to combine cutting-edge generative AI research with concrete impact on a strategic nuclear-energy challenge.  #CEA-List ; #Research Engineer You hold a PhD in Physics, Applied Mathematics, or Computer Science, with experience in deep generative models (VAE, diffusion) and Python/PyTorch. Applications from statistical physicists are welcome.  STILL HESITATING? The additional benefits of your mission might interest you: A cutting-edge research ecosystem, unique in its field and dedicated to high-impact societal themes, giving meaning to your work.Training programs to strengthen your skills, acquire new ones, and enhance your mission.A work-life balance recognized by our team members.Remote work options to reduce commuting time and improve your quality of life.A rich employee benefits committee (CE) with social, cultural, and sports activities.A dynamic workplace at the heart of a vibrant hub, surrounded by schools and tech companies.  Interested? Apply—this position is perfect for you!  In line with the CEA’s commitment to inclusivity, this role is open to all. The CEA offers accommodations and/or organizational adjustments to support workers with disabilities.