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Schrödinger equations, based on nonlinear approximations such as low-rank tensor decompositions, Gaussian mixtures and neural networks, with a particular focus on the computational costs of reliable solvers
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of Computation, Information and Technology at the Technical University of Munich (TUM) welcomes applications for a PhD or Postdoc Position (m/f/d, 100%, 2 years+) in Numerical Mathematics. Field of Research
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Postdoc (f/m/d): Machine Learning for Materials Modeling / Completed university studies (PhD) in ...
findings at academic venues and publish research in peer-reviewed journals Your profile # Completed university studies (PhD) in the field of Physics, Computer science, Materials science, Chemistry, or a
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Researcher The position is being offered within the research project "Combinatorial and Implicit Approaches to Deep Learning”, which is part of the Priority Programme "Theoretical Foundations of Deep Learning
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Physical Oceanography and Instrumentation, Marine Chemistry, Biological Oceanography, Marine Geosciences, and Marine Observations works interdisciplinary within a joint research program. What will be your
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number: 2025-0107 We have an open postdoctoral position in the Division “Personalized Medical Oncology” (head: Prof. Sonja Loges MD, PhD). The Department “Personalized Medical Oncology” focusses
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The Network Analysis and Modelling group investigates how genetic variation shapes gene regulation, protein function, and, ultimately, observable plant traits. Using machine learning and network
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consortium partners Your Profile: Excellent PhD in electrical engineering, computer science, or a related field Proven track record of high-level research, demonstrated through peer-reviewed publications and
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side projects and build networks inside and outside the institute Analyze diverse data sets for multi-omics integration in plant genetics Expand expertise and collaborations beyond plant research Our Lab
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species Perform bioinformatics and computational analyses to identify microbiome-lifespan relationships Apply rigorous molecular biology methodologies to elucidate mechanisms underlying microbiome effects