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Field
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programming skills in Python; initial experience with machine learning frameworks such as PyTorch or TensorFlow Initial practical experience from a master's thesis, study projects, internships, or open-source
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geochemistry, planetary science, archaeology, environmental science, and forensic research. The NIGEL facility (https://nigel.amsterdam/ ) headed by the MAGMAS PI is unique in the Netherlands with 2 TIMS, 2 MC
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to real-world engineering challenges. Computer Engineering or related disciplines, provided you have a strong interest in communication systems and networking. If you have a solid technical background and
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allow for more distributed and variable generation. Job requirements Essentials: Basic knowledge of power systems and machine learning/AI. Completed an MSc degree in a highly technical related discipline
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analyses or game theoretic analysis. Experience with large language models, machine learning, and/or programming in R or equivalent programs is an advantage but not a requirement. The evaluation of
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, sensors and instrumentation. Knowledge of one or more of the following areas:Power electronics, Reliability and failure mechanisms, Sensors and instrumentation, Data analytics, machine learning, or AI
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practical machine learning/artificial intelligence courses and relevant project and thesis experience. You have a keen interest in AI alignment, human-AI interaction, and explainable AI, and enjoy
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scientific excellence and applied research to design solutions that address real-world challenges and create positive impact. Do you want to know more about LIST? Check our website: https://www.list.lu/ You
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Beginning Winter semester Application deadline All students – online application: 1 March for the following winter semester https://www.lmu.de/psy/de/studium/doctoral-training-program-in-the-learning-sciences
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team includes: Prof. Ivan Depina – main supervisor and coordinator, probabilistic modelling, scientific machine learning Prof. Mohamed Hamdy – building performance simulation, building automation