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applications based on the following skillsets. If you do not fullfil all requirements, please still apply (there is room for learning-on-the-job). An engineering degree, preferably, aerospace or mechanical
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(or equivalent) to model neutron transport and tritium breeding behaviour within breeder blanket configurations. The project will then extend toward accelerated predictive methodologies using machine learning and
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should ideally have experience in: Essential Deep learning and machine learning Computer vision Python programming PyTorch or TensorFlow Strong mathematical and analytical skills Desirable Video
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health. Successful candidates may have experience in electron or X-ray microscopy, image analysis, AI and machine learning, quantitative data science or computational modelling. They will be able to work
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programming, e.g. Python or MATLAB, and an interest in concepts from reservoir computing or machine learning, is welcome A genuine interest in interdisciplinary research at the interface of biology, engineering
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, Machine Learning, or Smart Energy Publication record in peer-reviewed journals or conferences, commensurate with stage of career Good programming skills in Python, R, Java, or Matlab Experience
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, including a mixture of classical and quantum mechanics simulations, cheminformatics and machine learning, as well as collaborative software development, providing expertise for a broad range of future careers
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heterogeneity govern transport dynamics and degradation mechanisms during extended operation. A coupled mechanical–transport framework, accelerated through machine-learning surrogate models trained on multiscale
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degree in computer science, mathematics, statistics, physics or relevant fields. Strong background in machine learning, preferably experience in probabilistic modeling, Bayesian machine learning, or graph
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skills. Fluent in English, both spoken and written. Willing to learn the Dutch language. TU Delft (Delft University of Technology) Working at TU Delft means contributing to solutions that really make a