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doctoral programme in Health Data Sciences for outstanding junior researchers is to provide a structured framework of studies, research, and teaching for promising scientists in the disciplines of Health
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hardware and software Adapt algorithms for effective performance on neuromorphic hardware Knowledge in at least one area as a plus: deep learning hardware development memory technology Strong problem-solving
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Computer-adaptive methods and multi-stage testing Application of machine learning in psychometrics Predictive modeling of educational data Methodological challenges in cohort comparisons Advanced meta
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for a doctoral candidate with the following qualifications: Master's degree in meteorology, physics, mathematics, computer science or an equivalent scientific or mathematical discipline Very good
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documents. Please send them by e-mail to marius.henkel@tum.de Technical University of Munich Prof. Dr.-Ing. Marius Henkel | Assistant Professorship of Cellular Agriculture | TUM School of Life Sciences Gregor
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, neuroscience, biomedical sciences, or a related field A keen interest in neurophysiology, epidemiology, and the neuroscience of neurological and psychiatric conditions Solid experience in experimental research
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, veterinary medicine, pharmacy, natural science, or in another subject area with a biomedical or health-relevant focus The degree must entitle the applicant to pursue PhD studies in Germany. (Verification
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, both written and verbal Knowledge of German and/or a willingness to learn Computer/programming literacy, for example in R, and/or software used in image processing (Adobe Photoshop, ImageJ etc.) Ability
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RPTU University of Kaiserslautern-Landau • | Kaiserslautern, Rheinland Pfalz | Germany | about 4 hours ago
time before the dissertation is therefore shortened. The acquisition and application of computer science knowledge to research problems are facilitated when students enter the programme early
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research questions from several fields such as software and domain engineering, system modelling and analysis, application adaptability and integration, human computer interaction, security, and