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-based metadata platform that you will help develop. In collaboration with stakeholders from energy research, you will develop methods to increase data and software interoperability, enabling the automated
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to increase data and software interoperability, enabling the automated reuse of energy systems analysis processes. In line with FAIR and Linked Open Data principles, you will design interfaces that enable
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participation in top international conferences to present your work Participate in yearly retreats organized by the doctoral network participants Support the dissemination of software tools and concepts Supervise
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Infrastructure? No Offer Description Work group: PGI-15 - Neuromorphic Software Eco System Area of research: Promotion Job description: Your Job: The conventional, manual co-design of algorithms and hardware is
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Your Job: Reinforcement Learning (RL) is a versatile and powerful tool for control, but often data-inefficient, requiring numerous updates and non-local information such as replay buffers and batch
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internships at KU Leuven (Prof. Rodolphe Sepulchre) and at TU Delft (Prof. Charlotte Frenkel) Participate in yearly retreats organized by the doctoral network participants Support the dissemination of software
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academic and industrial cooperation partners Requirements: excellent university degree (M.Sc., Diploma) in either computer engineering, computer science, electrical engineering or any related natural science
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30.06.2025, Wissenschaftliches Personal The Chair of Software Engineering for Business Information Systems (sebis) at the Technical University of Munich is looking for outstanding candidates
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@rwth-aachen.de Requirements Research FieldEngineering » Civil engineeringEducation LevelMaster Degree or equivalent Skills/Qualifications MSc. degree (or equivalent) in Civil Engineering, Structural
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engineering, structural dynamics, basic isolation, finite element modelling. Proficiency and/or interest in programming languages (e.g. MATLAB, Python, R) and software platforms such as OpenSees, ABAQUS, LS