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on cutting edge machine learning methods? If you are establishing a career as a researcher in machine learning, and you are motivated to work with the latest methods for quantifying uncertainty in neural
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assessments. The exceptional availability of Danish Big Dataset on health outcomes, consumption and sustainability. A unique combination of mass balance-based Source-to-Impact Models and Machine Learning
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multiscale modelling techniques, machine learning methods, and self-driving laboratories to accelerate the discovery of novel materials for energy applications. The candidate will work in a highly
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, in the new Photonic Integrated Circuit based Systems (PICSys) group. PhD scholarship in Machine Learning Techniques for Spectral Shaping of Ultra-Broadband Optical Frequency Combs - DTU Electro Kgs
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the PhD Alliance 2024 initiative at DTU, in collaboration with Cornell University, USA. The AMD section is a leading group in combining multiscale modelling techniques, machine learning methods, and self
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fascinated by the possibilities of employing neural networks in computer vision? Would you like to develop methods with the potential to address critical societal challenges? Would you thrive in an innovation
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physical simulations and machine learning techniques, you will investigate the ability of surrogate models to determine large wind farms’ efficiency and wake characteristics, as well as the wake model
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of surfaces in 3-space is an essential prerequisite. Knowledge of computational geometric algorithms, optimization, and machine learning techniques would be favourably regarded. Position 2: You will focus
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nature. The groups of the Section cover a wide variety of subjects ranging from personalized medicine where we, amongst others, predict the optimal treatment based on an individual’s genome, to machine
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for Power and Energy Systems (PES). The EMA Section has a strong multi-disciplinary research focus on energy markets, optimization, game theory, and machine learning. We are currently 14 members in the EMA