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<span lang="en"> Helmholtz-Zentrum Hereon</span> | Geesthacht, Schleswig-Holstein | Germany | about 13 hours ago
characterization.
The objective of the project is to bridge the gap between purely data-driven materials modeling and mechanistic microstructure simulations by combining crystal plasticity, dynamic
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. Ransell D'Souza at the Department of Chemistry and Materials Science, Aalto University, and the Data-driven Atomistic Simulation (DAS) group, led by Prof. Miguel Caro at the Department of Chemistry and
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Research Assistant (m/f/d) with a Ph.D. in Civil Engineering, Engineering Physics, Physics, Mathemat
of model parameters from experimental and operational data under uncertainty using these metamodels Development of data-driven approaches for modeling residual prediction uncertainties and model-form
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geophysics, seismology, data science, artificial intelligence, applied mathematics, physics, and related fields. Candidates with strong methodological expertise and an interest in applying AI to Earth
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geophysics, seismology, data science, artificial intelligence, applied mathematics, physics, and related fields. Candidates with strong methodological expertise and an interest in applying AI to Earth
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with candidates who are highly motivated, reliable, self-driven, and with a background in experimental physics, electromagnetics, or quantum optics. Other qualities of the successful candidate: Is
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executed, ideally involving 3D image analysis, inverse problems, or physics-informed modeling. Cryo-EM/ET and computational structural biology projects are especially relevant. Discuss results
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future. They represent individuals driven by curiosity and a relentless pursuit of excellence. With us, they find the space to try things out and unfold their potential. Are you inspired by their
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known, data are noisy and sparsely sampled, measurements vary across individuals and conditions, and some relevant biological states are unobserved. Purely data-driven models offer flexibility, but often
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and conditions, and some relevant biological states are unobserved. Purely data-driven models offer flexibility, but often ignore known biology and provide limited insight into uncertainty and