65 postdoc-in-thermal-network-of-the-physical-building PhD positions at Delft University of Technology (TU Delft) in Netherlands
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Consolidator project “Systemic physical climate risk in complex adaptive economies” (SPHINX) made possible thanks to the European Research Council. Join our ERC SPHINX Team to elicit how people and businesses
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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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outside the lab that account for sex variations. In collaboration with societal, industry, and health partners—including NOC*NSF, Vitronic, ModelHealth, and the Sport & Gyn network—these next-generation
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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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and students are working to improve the built environment with the help of a broad set of disciplines, including architectural design, urban planning, building technology, social sciences, process
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24 Nov 2025 Job Information Organisation/Company Delft University of Technology (TU Delft) Research Field Mathematics » Computational mathematics Physics » Applied physics Physics » Quantum
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, these qualities are indispensable for a fulfilling PhD journey. These experiences will build you as an independent researcher, expand your professional network, and pave the way for diverse career pave the way
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Description Are you excited about building cybersecurity platforms that are secure, explainable, and compliant by design? Do you want to combine real-time authorization, distributed ledgers, and verifiable
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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