67 postdoctoral-image-processing-in-computer-science PhD positions at Technical University of Munich in Germany
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13.02.2025, Wissenschaftliches Personal The Professorship of Machine Learning at the Department of Computer Engineering at TUM has open positions for a doctoral researcher (TV-L E13 100%, 3-4 years
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15.04.2025, Wissenschaftliches Personal The Lab for Artificial Intelligence in Medical Imaging (www.ai-med.de) is inviting applications for a fully funded PhD position in interpretable machine
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of Engineering and Design. Our teaching and research focus lies on computer-based development of engineering products, particularly on the planning and realization of built facilities using computational modeling
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encouraged (e.g. South America, Asia or Africa). The PhD process will be accompanied by in-tegration into TUM’s School of Life Sciences or School of Management and participation in the related Graduate School
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processes regulated by AGC1 kinases. The Chair of Plant Systems Biology has strong expertise in all relevant molecular, cell biological, biochemical, physiological and genetic techniques. The group also has
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journals. Close collaboration with team members and colleagues. Essential qualifications: M.Sc. in Computer Science, Machine Learning, or equivalent with interest in Medical Imaging and Deep Learning. Strong
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: M.Sc. in Computer Science, Machine Learning, or equivalent with interest in Medical Imaging and Deep Learning. Strong knowledge in Machine/Deep Learning with experience in discriminative models
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The position is available as soon as possible. We offer thorough training in: - Performing a wide spectrum of molecular, cell biology-related and computational methodologies and techniques, such as primary cell
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of results in peer-reviewed journals and presentation at international conferences. Requirements: Above average Master’s degree in engineering, applied mathematics, physics or computational science Good
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(https://soilsystems.net/ ), a Priority Programme (SPP 2322) funded by the Deutsche Forschungsgemeinschaft (DFG; German Research Foundation). Within SoilSystems, scientists from different disciplines from