85 postdoctoral-computational-"Multiple" PhD positions at Technical University of Denmark in Denmark
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optimization. Experience with energy system modeling - ideally of large scale multiple country energy systems, PtX and renewable fuel production. Strong writing and presentation skills. A willingness and desire
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qualifications As our new colleague in our research team your job will be to develop novel computational frameworks for machine learning. In particular, you will push the boundaries of Scalability, drawing upon
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development and marine management. Your primary tasks will be to: Compile and harmonize data from multiple sources (e.g., EMODnet, Copernicus, fisheries surveys, citizen science). Engage with data managers and
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, including electrical engineering, control theory, industrial engineering, electronics engineering, energy policy, data science, and applied mathematics. As part of the Alliance program, your project will be
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oxidation and disinfection processes. Work together with researchers at multiple departments at DTU and NTNU Research activities will mainly be carried out at DTU Sustain with research visits in Norway
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samples, by the development of advanced computational multiphysics models of stress corrosion cracking and coupling these with process-microstructure models (being developed within MicroAM project). Main
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collaborative settings and wish to play a key role in an EU-funded project with researchers from multiple countries? If so, this PhD position could be a good opportunity for you. This project focuses
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of diverse teams with multiple technical and theoretical expertise. Applicable responsibilities for both positions: You are expected to be able to organize and perform your own experiments, and critically
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Research Framework Programme? Horizon Europe - MSCA Reference Number DC6 Marie Curie Grant Agreement Number 101225914 Is the Job related to staff position within a Research Infrastructure? No Offer
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modeling of complex information systems, and SDU and the Royal Danish Defence College’s established intelligence studies and practice. By introducing computational modeling to traditional intelligence