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and hydrogen storage to maximize energy efficiency while keeping the grid reliable and secure. Our research method is engineering-oriented, prototype-driven, and highly interdisciplinary. Our typical
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to maximize energy efficiency while keeping the grid reliable and secure. Our research method is engineering-oriented, prototype-driven, and highly interdisciplinary. Our typical research process includes
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. Contact Prof. Holger Boche, Technical University of Munich, School of Computation, Information and Technology, Chair of Theoretical Information Technology, Theresienstrasse 90, 80333 Munich. https
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technical field, such as mechanical engineering, computer science, transportation systems, or civil/environmental engineering with a focus on traffic engineering, with very good grades. You bring solid
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to study translational aspects of cancer (single-cell sequencing of immune cells, organoid co-cultures, cellular engineering via CRISPR/Cas9 technology, in vivo imaging, advanced animal models of allo-SCT
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for an exciting new computing paradigm involving the development of innovative solutions Openness to communicate, cooperate and exchange ideas within a joint endeavor of multiple vibrant research teams Our offer A
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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 knowledge in Machine/Deep
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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, adversarial attacks, and
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, organization, compression, analysis, and visualization of georeferenced or geometric data in large scales. We put emphasis on methods of distributed computing, machine learning, image and text analysis
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domain. You should have completed your Master/Diploma studies with top grades in Computer Science, Mathematics, Engineering, Chemistry, Physics or a similar subject. Most importantly, you should be