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secondments Salary Gross amount (per month) Living Allowance EUR 5470 Mobility Allowance EUR 710 Family Allowance EUR 660 GreenFieldData Project at glance : “IoRT Data management and analysis for Sustainable
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-scale compound drivers. We will leverage machine learning methods to bridge the gap between drivers at coarse model resolutions and impacts captured by high-resolution observations. Job description Arctic
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-disciplines; to promote and inspire discovery and learning that enhances patient care; and to contribute to the translation of scientific progress into clinical practice. The Department of Physiology consists
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Leibniz-Institute for Food Systems Biology at the Technical University of Munich | Freising, Bayern | Germany | 3 months ago
new insights into food-effector systems, sophisticated and tailored computational methods are needed. This project aims at combining probabilistic machine learning methods with prior knowledge in
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Research as a Researcher — your employment with Ericsson continues without interruption. What you will do: Ericsson Research develops and evaluates new concepts and standards for future mobile communications
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on AI-supported decision-making that contribute to the empowerment and democratic participation of citizens. The project addresses real-world challenges across domains such as healthcare, mobility
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proteolysis-targeting chimeras (PROTACs). We will benchmark their performance and determine specificity using established reporter cells, engineered primary murine AML cells and a panel of human AML cell lines
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mechanisms occurring in these materials and their synthesis over all relevant length scales (e.g., cutting-edge ab initio methods, atomistic simulation methods, multi-scale modelling, machine learning) High
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, and training methods - across multiple technological platforms - photonics, electronics, biological neurons. Responsibilities and tasks This PhD project aims to develop, verify, and benchmark learning
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– from the modeling of material behavior to the development of the material to the finished component. PhD position on physics-based machine learning modeling for materials and process design Reference