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at the interface of probability theory and artificial intelligence, whose goal is to rethink and structure the way mathematical research is produced in the era of AI. Key Responsibilities: Designing and implementing
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expertise. Your Responsibilities: Conduct research in the field of Multiscale Computational Methods for novel metamaterials as described above Develop theories, methods and computational tools Participate in
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approaches to transform unstructured bug reports into actionable insights that connect to code, support diagnosis, and improve the speed and quality of fixes. Application areas include developer tooling
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above Develop theories, methods and computational tools Participate in project meetings / secondments Collaborate with external industrial and academic partners Disseminate research findings through
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. Our research brings together social theory, empirical studies guided by a range of interpretive methodologies, and the critique as well as advancement of interventions and social policies. We
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candidate will work on Bug Report Intelligence for the Generative AI Era (BRIDGE) - exploring approaches to transform unstructured bug reports into actionable insights that connect to code, support diagnosis
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ML frameworks like PyTorch/JAX Genuine interest in MLFFs, simulation methods, and foundational ML research Desired skills: Experience with atomistic simulation codes: ASE, FHI-aims, VASP, CP2K
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Luxembourg) Guidance of a team of student assistants Conceptualizing and implementing behavioral analyses of video-recorded parent-child interactions (e.g., development of coding manuals, training and