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implementation of these within optimized computer code, but also large-scale applications of the resulting methods to various chemical problems of interest. Candidates with a strong background in theoretical and
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production and quality control will help save natural resources as well as reduce waste material and energy consumption. Formulation and test methods using mathematical modelling and prediction tools. Fouling
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on post-training methods for these low-resourced languages, for example, by investigating the role of synthetic data, among other data augmentation techniques, and the role of in-context learning in
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program and at the AU Summer University You will be under daily supervision by group leader Rasmus O. Bak, and you will formally report to the Head of Department Thomas G. Jensen. Your competences You have
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Postdoc in development and testing of electrodes for liquid alkaline water electrolysis - DTU Energy
electrochemical testing by means of various voltametric methods and electrochemical impedance spectroscopy. As a formal qualification, you must hold a PhD degree (or equivalent). We offer DTU is a leading technical
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(e.g., based on physiological signals or direct inputs from occupants) and developing algorithms, including machine learning methods. The work will include statistical modelling, data-driven modelling
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performing educational research (mix-methods, surveys). Your primary tasks will be to: Implement full-stack applications, including an AI model in the back-end and GUI (in HTML); Deploy AI models both locally