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-tuning, or related optimization methods. Experience with cloud infrastructure, MLOps or LLMOps, containerization, or production deployment. Frontend and/or backend development skills. We offer ETH Zurich
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, NTNU, will host the PhD position. The topic of the PhD fellowship is at the interface of numerical mathematics, generative AI models, and computer science. A successful candidate will be offered a three
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 3 months ago
of existing approaches. The existing detection criteria target changes of elastic stability, which can be computed either by using the optimal control theory or analyzing the Hessian matrix of the robot
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University is home to numerous world-class research groups and institutes, and maintains strong connections with leading research organizations. CML is part of the Faculty of Science at Leiden University
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Heidelberg Institute for Theoretical Studies (HITS gGmbH) | Heidelberg, Baden W rttemberg | Germany | about 7 hours ago
interdisciplinarity, implemented in numerous cross-group and cross-disciplinary projects. The base funding of HITS is provided by the Klaus Tschira Foundation. HITS is looking to fill a fully funded PhD position (m/f/x
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or more of the following topics: numerical methods for (partial) differential equations. optimization or inverse problems. data assimilation or uncertainty quantification. agentic and generative AI. solid
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aspect of cybersecurity including human motivation, behaviour, usable and accessible design, policy and governance that is leading to non-optimal cyber resilience within a particular context. Malware and
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optimal ways to schematize and parameterize the subsurface at local to regional scales to assess dike safety using geological and geohydrological data and models, for characteristic fluvial landscapes in
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will feed into an automated stope design workflow, producing variable-length, locally adaptive geometries that optimize the balance between stability, recovery, and dilution control. Through
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research on exciting projects and develop customised products and services for our clients from numerous industries and the public sector. The overarching topics at Fraunhofer ITWM are machine learning