158 parallel-and-distributed-computing-"Multiple" positions at Technical University of Denmark
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conducts cutting-edge research in chemical and biochemical engineering, with a strong focus on sustainable technologies. As part of our commitment to addressing climate challenges, we operate multiple carbon
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increasing the value of such a hybrid power plant for uncertain renewable energy driven future power systems. You will need to work closely with industry in multiple national and international research
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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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to plan and carry out complicated tasks and to pursue parallel paths able to accommodate strict time boundaries imposed by the overall project goals excellent at communicating and reporting your work in
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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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on the modelling and optimisation of PRO systems using advanced Computational Fluid Dynamics (CFD) and Machine Learning (ML) techniques. This role offers an exciting opportunity to contribute to cutting-edge
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interest and documented skills and experience in using computer-based tools to analyse, simulate and predict capture performance of active and passive fishing gears. A track record of publishing in peer
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process. An integral part of the project will be the development of enhanced data-driven physics methods to achieve reliable prediction of material removal rate and material removal distribution
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performance computing) services. We are looking for a new colleague for a newly established position, someone with insight into and interest in the technical aspects of FAIR data management solutions and
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driving rapid growth in distributed energy resources (DERs), the electrification of transport, heating, and water systems — and the rise of hyperscale data centers. Coordinating these heterogeneous active