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Max Planck Institute of Molecular Cell Biology and Genetics, Dresden | Dresden, Sachsen | Germany | 2 months ago
experience Experience in computer programming; Experience of computational mathematics or data analysis Experience with interdisciplinary applications in biology Our offer A full—time position, with a flexible
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' to develop neural networks with remarkable information content: flies, which we use as a model, have brains that compute flying in 3D, navigation, metabolism and advanced learning and memory capabilities - all
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into neuroendocrine output to instruct adaptive physiology and behavior. Conversely, we seek to understand how internal states shape our physiological responses to the same cues. Our research is based on the premise
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verification scalable and reliable. Learn more about logical zonotopes: [paper link ] | [talk link ]. You will conduct original research on logical zonotope based methods for model checking and digital circuit
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on the design and evaluation of innovative data- and machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization
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Coordinating and instruct a practical course for BSc Biochemistry students and supervise MSc students in the lab Your qualifications: PhD in Biochemistry, Biology or Life Sciences Strong motivation and a genuine
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the faculties of medicine and computer science at TUM, as well as the Munich Center for Machine Learning (MCML). It is a great place for interdisciplinary research between medicine and data science. We
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(e.g. via machine learning) to qualitative analyses (e.g. via interviews) to support ambitious policies for climate and energy transitions. This position Green hydrogen is key to decarbonizing many hard
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) in materials science, biotechnology, microbiology, bioinformatics, life sciences, engineering, or comparable field with completed doctorate Experience with AI-supported modeling (e.g., Scikit-Learn
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, nationality, ethnicity, sexual identity, physical abilities, religion or age. Qualified applicants with physical disabilities will be given preference. Learn more about diversity at Helmholtz Munich Our