12 programming-language Postdoctoral research jobs at Technical University of Munich in Germany
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, currently listed as the strongest German business school for research, and #9 in Europe for M.Sc. programs on entrepreneurship. The TUM Campus Heilbronn is a dynamic organization whose goal is to achieve
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research studies for automated image analysis. In particular, you will: Plan, develop, and implement AI/ML algorithms for pathology image analysis. Integrate multi-modal data (e.g., genomics, clinical data
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institutions. You support us in making this cooperation efficient and productive. As Research Associate you will also support our teaching activities in several Bachelor and Master programs offered by the School
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institutions. You support us in making this cooperation efficient and productive. As Research Associate you will also support our teaching activities in several Bachelor and Master programs offered by the School
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for livestock systems in East Africa, and in the subtropics in Latin-America. The research programme will examine productivity of grasslands, nutrient stocks and cycling and their relationship to biodiversity. We
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of linear algebra and numerical optimization Understanding of statistical modeling and inverse problems is desirable Experience with programming languages like Python, MATLAB, or C++ Joy in dealing with
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of empirical research (quantitative or experimental) methods, • knowledge of statistics, programming languages (e.g., Python), natural language processing, machine learning is advantageous but not
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Institute (https://www.mdsi.tum.de/). The Position Plan, develop and test novel computational models for the analysis of digital pathology image data. Collaborate with pathologists and other domain experts
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the subtropics in Latin-America. The research programme will examine productivity of grasslands, nutrient stocks and cycling and their relationship to biodiversity. We conduct experiments in the field
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part of a degree program. In particular, knowledge about finite-element analysis is an absolute must . Familiarity with iterative solvers , preconditioners , multigrid methods , and mixed-precision