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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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<span lang="en"> Helmholtz-Zentrum Hereon</span> | Geesthacht, Schleswig-Holstein | Germany | about 7 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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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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fundamental Earth science and engineering applications . Research activities may involve geophysical forward modeling, AI-driven geophysical inversion, seismic monitoring and imaging, scientific machine
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fundamental Earth science and engineering applications . Research activities may involve geophysical forward modeling, AI-driven geophysical inversion, seismic monitoring and imaging, scientific machine
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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
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boundaries of science Strong English communication skills Additional skills that would be an advantage: Programming and data analysis experience Experience with working on high-performance computers
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, and modeling of neuroscience data and concepts. Proposals focused on disease mechanisms or that do not contribute to our understanding of non-disease states are not suitable for this call. Candidates