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people across disciplines and with a variety of perspectives and backgrounds. The Faculty external link has six departments: Biology, Pharmaceutical Sciences, Information & Computing Sciences, Physics
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observed in Drosophila larvae. This interdisciplinary project combines biology, neuroscience, and computational modelling to understand how the larva’s body’s physical properties influence its motor control
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at the single-cell level, using tools from optimal transport, mathematical optimization, and machine learning. In addition to method development, the work includes applying and benchmarking algorithms on both
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Job Description We invite applications for a fully funded PhD position focused on the development of advanced computer vision and machine learning algorithms for detection and identification
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the form of a human-expert informed reward function. Second, we aim for the integration of low-energy machine learning algorithms, so that the resulting AI model can run on a variety of devices, including
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and developmental biology, mechanobiology, stem cells and differentiation, network reconstruction and systems biology, proteomics, genomics, metabolomics, sequencing and algorithms, computational
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Media (EDM), the Research Training Group KD²School (KD²School), π³: Parameter Identification – Analysis, Algorithms, Implementations (RTG π³), the UBRA AI Center for Health Care , and the ZeMKI
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machine learning algorithms, so that the resulting AI model can run on a variety of devices, including UAVs (e.g. drones) that may be used in turbine inspection. The overall aim is the design of a portable
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PhD candidate in the automated detection of measurable residual disease in hematological malignancie
of measurable residual disease. Join our vibrant research environment and contribute to pioneering projects in bioinformatics and computational biology! Project overview Measurable residual disease (MRD) is an
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to mastering the great challenges facing society today. At the Institute of Radiooncology – OncoRay scientists (f/m/d) specializing in medicine, physics, biology and IT work together to crucially improve