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candidates hold a Master’s degree in Informatics, Mathematics, or a related field, and possess strong expertise in linear algebra, GPU architectures, and programming in C++ and Python. This is a 100% TVL E13
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-based AI for multidisciplinary tumor boards. The successful candidate will develop LLM-based pipelines, semantic harmonization, and transformer-based temporal models on a large multimodal oncology dataset
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-generation multimodal foundation models for digital patient twins in oncology and cardiovascular medicine. The position is part of the EU Horizon Europe project TWIN-X, Digital Twins with Generative AI
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, energy systems, computational engineering, or a related field Strong background in numerical methods, mathematical modeling, and network simulation or analysis Good understanding of power systems, gas
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Heidelberg Institute for Theoretical Studies (HITS gGmbH) | Heidelberg, Baden W rttemberg | Germany | about 7 hours ago
as a private, non-profit research institute. HITS conducts basic research in the natural sciences, mathematics and computer science with a focus on the processing, structuring, and analyzing of large
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(www.denkglobaldx.org ), our department hosts a diverse and interdisciplinary team working across diagnostic innovation, clinical and implementation research, mathematical modelling, data science, and health-economic
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German Cancer Research Center in the Helmholtz Association (DKFZ) | Heidelberg, Baden W rttemberg | Germany | 2 months ago
across large genomic datasets. We focus on cancer models (osteosarcoma, breast cancer, leukemia) and on neural progenitor cells to understand how genome instability contributes to tumor initiation, therapy
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disturbance experiments at Trinity College Dublin and on modelling resilience and RD at University of Zürich are planned. Research Project DC3 DC3 will use empirical plankton ecology to analyze both
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 2 months ago
and advance statistical, image analysis, and machine learning approaches Develop interpretable models that reveal biologically testable relationships and generate new scientific hypotheses Independently
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, Mathematics, Physics, Engineering, Computer Science or related disciplines with a strong academic record. Strong background in data analysis, statistics, machine learning, scientific computing, or related