523 computational-complexity "NTNU Norwegian University of Science and Technology" PhD positions in Germany
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Universität Berlin. The position is part of the research group QUALITY.2 (Phytonutrient Management) in the programme area ‘Plant Quality and Food Security’ (QUALITY). The aim of the research project “PhytoM” is
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• Scientific publishing Your qualifications: • Completed academic university degree (university diploma / M.Sc.) in Computer Science, Geoscience, Physics, Data Science, or comparable subjects • Experience in
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program, which includes tailored training, workshops, retreats, and conference travel. You will have access to cutting-edge laboratories and theoretical methods, individual supervision, and a wide range of
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, giving rise to complex lesions. GSI is working on the quantification of such complex lesions in particular in dependence on radiation type. Within this program, the GSI biophysics department offers a PhD
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Artificial Intelligence – ScaDS.AI. We seek to fill the above position as soon as possible (e.g., Oktober 1, 2025). This interdisciplinary project investigates how physical systems can serve as computational
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of Europe’s biggest research centers and help us to shape change! Are you eager to pursue a four-year doctoral project that bridges scientific disciplines? Are you excited by complex societal challenges
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degree (or equivalent) in Data Science, Computational Biology, Bioinformatics, Computer Science, Physics or a related field Solid programming skills and knowledge in deep learning, statistical modelling
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Engineering, Operations Research, Civil Engineering, Computer Science, Data Science or a related field, from a university/department with a strong international research reputation Strong mathematical and
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interdisciplinary research team. We study tumor evolution and immune microenvironment adaptation by combining functional genomics, experimental model systems, patient samples, and computational biology (Brägelmann et
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. Applicants should have experience with tissue culture and standard molecular biology methods. Basic knowledge of computer programming (using the R software environment) and hands-on experience working with