56 postdoc-in-thermal-network-of-the-physical-building PhD positions at Delft University of Technology (TU Delft)
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electric power for the electric power system. To make the thermal cycle compact, the thermal cycle that drives the turbine - generator combination is a cycle with super critical CO2, which results a high
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AI-driven solutions for sustainable, efficient, and collaborative port operations of the future. Job description European seaports must achieve net zero emission by 2050 and 55% emission reduction
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, postdocs, and faculty members. Our group focuses on understanding and mitigating corrosion processes, and on the development of electrocatalysts and electrochemical sensors through the synthesis of materials
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a multidisciplinary team of three researchers (two PhDs and one Postdoc), and in close collaboration with major industrial and research partners, including ESA (European Space Agency), Airbus, Rolls
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storage of biofuel? Join us in guiding the Dutch Ministry of Defence through a safe energy transition! Job description You'll be working in the Corrosion Technology and Electrochemistry (CTE) group, part of
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coordination failures reshape decarbonization pathways. Your research will combine methods from network analysis and agent-based modelling of economic systems to trace how international material and financial
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PhD Position on Machine Learning Detection of Positive Tipping Points in the Clean Energy Transition
Infrastructure? No Offer Description Develop machine learning models to detect early signs of abrupt shift towards clean energy technologies and make climate action adaptive to this information. Job description
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Find2Fix will engineer the first open-source tool for the entire process
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make extensive use of low-fidelity simulations which can provide fast but inaccurate solutions depending on the flow complexity. To close this gap, this PhD will explore machine-learning (ML) methods
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. This simple unit is limiting the learning capabilities of recurrent neural network models in tasks characterized by multi-timescale and long-range temporal dependencies. To implement multi-scale adaptation, in