283 parallel-computing-numerical-methods-"Multiple" Postdoctoral positions in Germany
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on disaster risk management and climate adaptation, using probilistic risk modelling, applied statistical methods to evaluate risk management and adaptation measures in the agricultural sector, mainly in low
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Max Planck Institute of Molecular Cell Biology and Genetics, Dresden | Dresden, Sachsen | Germany | about 2 months ago
, physics, and computation. Currently about 500 employees from over 50 countries work at the institute in a highly collaborative and curiosity-driven environment. MPI-CBG has twice been awarded the title
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DWI-Leibniz-Institute für Interaktive Materialien e.V. | Aachen, Nordrhein Westfalen | Germany | about 2 months ago
39,83 Offer Starting Date 1 Feb 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No
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Dissemination Platform), as well as diverse central units (ROOTS Academy, Reflective Turn Forum, Methods Nucleus) to collectively pursue a research agenda targeting key parameters of socio-environmental
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of comparative social policy and comparative research methods. The applicant is expected to hold a PhD in Political Science, Sociology, Economics or a related discipline. Knowledge and experience in data
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. The candidate should have: a PhD in microbiology, molecular biology, biochemistry or related subjects strong interest in genome-wide functional genetic methods, such as transposon or CRISPR assays. Previous
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twin of sperm motility, and utilize it to develop a separation method. Your tasks will include: Performing computer simulations and matching them to experimental data Very close collaboration with
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combining experimental and computational approaches to: Characterize the evolution of cis-regulatory networks across primate brain development using novel single-cell omics methods Apply deep learning models
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and Oncology and provides numerous training opportunities with access to cutting-edge techniques. The location of Heidelberg offers state-of-the-art infrastructure in a highly collaborative environment
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propose to combine machine learning techniques with formal methods. We will focus on safe reinforcement learning of motion planning problems for autonomous vessels. Motion planning is particularly