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will be at the absolute forefront of combining GNSS and modeling the different contributions that courses solid Earth deformation where the main contributors are elastic deformation, glacial isostatic
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. We are looking for a skilled and motivated Computational Engineer to work on the development of numerical gyro-fluid edge turbulence models targeting magnetic confinement fusion devices. Our section
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dashboards, run reliability/sensitivity checks and validation tests for the combined model. Text/natural language processing support: collect government policy documents across countries and set up machine
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between DTU and KTH, combining advanced plasma modelling expertise to tackle one of the most dynamic challenges in energy science: improving fusion reactor performance through controlled powder injection
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create multi-fidelity predictive models that integrate data from quantum simulations and experiments, using techniques such as equivariant graph neural networks with tensor embeddings. We aim to train
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potential for exploiting temperature gradients for producing electricity and predict their long-term performance under real operating conditions. The project also includes modeling of heat transfer and
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Systems, you will work at the forefront of developing methods to unlock the value of flexible assets in the green energy transition. You will have the opportunity to transform market data and models
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interest in information processing in humans and computers, and a particular focus on the signals they exchange, and the opportunities these signals offer for modelling and engineering of cognitive systems