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Field
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: This PhD project will develop model- and data-driven hybrid machine learning material models that capture the complex, nonlinear, path- and history-dependent behaviour of materials. The goal is to create
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: This PhD project will develop model- and data-driven hybrid machine learning material models that capture the complex, nonlinear, path- and history-dependent behaviour of materials. The goal is to create
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, electrical & electronic engineering, or equivalent. Background knowledge in signal representation/processing, visual data compression, and data-driven and machine learning/analysis. Prior research experience
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: PhD in nuclear engineering, applied physics, computational science, or a closely related field; demonstrated experience in Multiphysics modelling, numerical methods for PDEs, and code verification and
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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components are in use. More specifically, the PhD position will look towards connecting different advanced software tools (of multi-physics and data-based models) simulating the metal AM process
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17.07.2025, Wissenschaftliches Personal The Chair of Software Engineering & AI is searching for a new doctoral research associate (TVL-E13) in Generative Engine Optimization. Research focus
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20th August 2025 Languages English English English The Faculty of Technology, Natural Sciences and Maritime Sciences have a vacancy for a position as PhD Research Fellow in Energy Technology
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optimisation techniques and AI-based models to support decision-making in microgrid design and operation. Working in collaboration with a leading global mission critical firm of engineers, this project offers
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Organisation Job description In the Engineering and Technology Institute Groningen (ENTEG), we are looking for a talented and motivated PhD candidate on electrochemical ammonia synthesis in Protonic