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to ecological, ethical, and policy contexts. BioM will unite ecology, statistics, and philosophy to improve the modelling and governance of biodiversity under uncertainty. The project develops process-explicit
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | about 1 month ago
differences in cancers. The method is used to identify cancer clones in melanoma cases and support clinical decisions with deep molecular analysis of the detected tumor clones. The postdoc (f/m/x) will build
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pathology to resolve single cell heterogeneity and identify subtle cellular differences in cancers. The method is used to identify cancer clones in melanoma cases and support clinical decisions with deep
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linear algebra computations, building software for scientific applications using GPUs (Graphics Processing Unit), multi-threading and parallelism, numerical discretization methods (finite differences
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: to design GaN power components with their integrated functionalities. In close collaboration with the project consortium, the different devices will be studied using 1D and 2D finite element analyzes (e.g
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, computational biologists, developers, PhD students and researchers with different backgrounds. We always aim for an open and creative environment. The research group is based at the Center of Hematology and
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source areas. With the shifting focus of policy from deposition to emissions (target management), a better understanding of the processes in source areas has become crucial. Moreover, understanding what
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 2 months ago
least two different crop species in the same field), offers major agronomic potential. However, their implementation is still based on limited knowledge. As the production of experimental references is
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results. Machine Learning skills to automise comparison process. Unbiased approach to different theoretical models. Experience in HPC system usage and parallel/distributed computing. Knowledge in GPU-based
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for three consecutive periods (2014-2018 and 2018-2022 and 2023-2026). ICN2 comprises 19 Research Groups, 7 Technical Development and Support Units and Facilities, and 2 Research Platforms, covering different