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10.01.2022, Wissenschaftliches Personal The Chair of Computational Modeling and Simulation (CMS) at Technical University Munich invites applications for the position of a Research Assistant (m/f/d) for performing fundamental research in the frame of the project DrawOn funded by the Bavarian...
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PhD Position - Organic Electrosynthesis: monitoring of reaction transients with real-time techniques
between electrolyte-electrode interface structure and selectivity or efficiency of chemical outcome during the preparation of complex and value-added compounds directly from the readily available feedstock
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Dortmund, we invite applications for a PhD Candidate (m/f/d): Multidimensional Omics Data Analysis You will be responsible for Prediction of metabolic activity in complex microbial communities, leveraging
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The Weierstrass Institute for Applied Analysis and Stochastics (WIAS) is an institute of the Forschungsverbund Berlin e.V. (FVB). The FVB comprises seven non-university research institutes in Berlin
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WIAS Berlin, Weierstrass Institute for Applied Analysis and Stochastics Position ID: 2306 -PHD [#26752, 25/11] Position Title: Position Location: Berlin, Berlin 10117, Germany [map ] Appl Deadline
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Description The Weierstrass Institute for Applied Analysis and Stochastics (WIAS) is an institute of the Forschungsverbund Berlin e.V. (FVB). The FVB comprises seven non-university research
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. Qualification and Experience: You have a degree (Diploma, Master's) in physics, nuclear physics, radiochemistry, or a related field. Experience in operating complex experimental setups and using data analysis
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learning and data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms
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the testing of newly devel-oped materials and the use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission
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, Heidelberg and Mannheim, our researchers harness interdisciplinary collaboration to decipher the complexities of disease at the systems level – from molecules and cells to organs and the entire organism