120 parallel-computing-numerical-methods-"Simons-Foundation" PhD positions at DAAD in Germany
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that demand interdisciplinary solutions? Then the Program for Collaborative Doctoral Projects is the perfect opportunity for you. Many of today’s most pressing problems can only be tackled through
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consistent scientific methods for mobility planning and management, (2) integrate a new set of modular metrics for responsible mobility, (3) embed the planning methods into the open data AgiMo Digital Twin, (4
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available in the further tabs (e.g. “Application requirements”). Objective The programme aims at fostering strong, internationally oriented higher education systems in Southeast Asia with the capacity
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available in the further tabs (e.g. “Application requirements”). Objective The programme aims at fostering strong, internationally oriented higher education systems in South Asia with the capacity
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atomistic simulations, high-performance computing, and the application of AI-based methods Basic knowledge in photovoltaics and solid-state materials for energy application Ability to work individually and in
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reflects the organic pollution load in water. Current COD determination methods are often discontinuous or spectroscopic and impractical for real-time application, limiting their utility in dynamic, data
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Universität Berlin. The position is part of the research group QUALITY.2 (Phytonutrient Management) in the programme area ‘Plant Quality and Food Security’ (QUALITY). The aim of the research project “PhytoM” is
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Artificial Intelligence – ScaDS.AI. We seek to fill the above position as soon as possible (e.g., Oktober 1, 2025). This interdisciplinary project investigates how physical systems can serve as computational
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methods on identical locations, to investigate their structural, morphological and functional properties. Able to work independently, in a team and collaborate with other researchers and mentor junior
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hydrological modelling methods that explicitly use interpolation to pre-process precipitation data. In addition, the research should explore the integration of opportunistic sensor data to improve forecast