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challenges of our time. Be part of change As part of the interdisciplinary “Machine Learning Enhanced Sensor Systems” team, you will work on and develop data-driven solutions for intelligent sensor technology
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metabolic research is desirable, Experience using flow cytometric approaches (FACS) and/or animal experiments would be beneficial but is not required, Experience in evaluating ‘Omics’ data sets, especially
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Max Planck Institute for Legal History and Legal Theory, Frankfurt am Main | Frankfurt am Main, Hessen | Germany | about 4 hours ago
description of the graduate school and more detailed information on applications can be found at www.organizingarchitectures.org . We are also offering an online information event where we will present
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of evolutionary anthropology and medicine (W2) to be filled at the earliest possible date. The professorship will represent the field of population genetics in both research and teaching. Its focus is on the data
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macromolecular dynamics with machine learning, statistical mechanics, molecular simulations, and experimental data. The joint project “FAIME – Flexible and Efficient AI-driven Molecular Simulation Engine” is part
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our group "Computer Vision and Machine Learning" in developing AI models and transferring them into production. In the master's thesis "Exploring latent spaces of deep networks for fault analysis in
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background information about the programme can be found here ). Who can apply? Graduates and postgraduates from Sub-Saharan Africa with a first academic degree if applying for a Master’s programme, or with a
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research focus on collecting new data through excavations and survey campaigns in Germany, South-Eastern and Eastern Europe, and neighbouring regions of Eurasia, and on the scientific evaluation
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and IPP as institutions. To ensure compliance with data protection regulations, applications should be submitted via our online system and include a cover letter, a resume, and a list of publications
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analysis of existing long-term biological, chemical and physical monitoring data of German Baltic Sea coastal waters. Compilation and analysis of existing phytoplankton monitoring data with a focus on