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/biomedical engineering or of relevant scientific field A solid background in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning packages
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imaging. Your Profile: * Master's degree in Computer Science, Electrical and Computer Engineering, Mathematics, Physics, or a related field * Strong background in mathematical and computational sciences
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host chromatin pathways (DFG Research Unit DEEP-DV, FOR5200). The group uses experimental infection systems, an array of high-throughput sequencing methods, and single-molecule live-cell imaging
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imaging. Your Profile: The successful applicant must have the following: • Master’s degree in physics, biophysics, biomedical engineering, computer engineering or electrical engineering. • Excellent track
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sensing of atoms in the MLT. The lidar will be used for the first dedicated search for atomic species that are so far undetected in the interface of atmosphere and space. Modern image analysis tools shall
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Optimization (DPO) and reinforcement learning from human feedback, building preference datasets together with clinicians - Build and run a Red Team process with physicians, computer scientists, and patient
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of mathematical models to the development of new imaging-related techniques and compounds. The programme is searching for excellent students who hold a Master's degree in Biology (or related fields), Physics
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, data science, applied mathematics, physics, materials science, or a related field. Solid background in machine learning and/or computer vision. Interest in representation learning, active learning
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and imaging diagnostics. The degree of resolution – already at single-cell level – will continue to increase in all disciplines of life sciences, and the need to process and combine huge data sets
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science and information science techniques. Several areas of computer science and mathematics play important roles: data management and engineering, machine learning and data analytics, signal and image