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the top 10% of their class in MSc and BSc, and have exceptional grades; should have a background in microwave engineering and machine learning; should have strong communication skills and be fluent in
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background in the topics related to this PhD position. Good knowledge of combinatorial optimization (scheduling problems, mathematical modelling etc.), machine learning and/or strong programming skills
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. These methods will integrate machine learning techniques and real-time sensor data, to enhance operational efficiency, reduce costs, and ensure desired service levels, such as meeting a high percentage of demand
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both independently and as part of an international, interdisciplinary team Assets•Experience with computer vision or deep learning (e.g. PyTorch, TensorFlow)•Familiarity with street view imagery or other
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signal processing and machine learning algorithms, have strong interpersonal skills and the ability to work in an international team. Experience in wireless communication and networking fundamentals is a
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, Mechanical), Computer Science, Applied Math/Statistics, Physics—or related. Candidates who will graduate in the near future are also welcome to apply. Strong foundation in machine learning/deep learning and
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familiar with data science and machine/deep learning toolkits. Experience with model deployment and the usage of MLOps tools (Dockerization, CI/CD pipelines, edge infrastructure, etc.) is a plus. As a PhD
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machine learning You have good programming skills in Matlab, Python You have proven your proficiency in English language equivalent to B2 level You are enthusiastic and result oriented You can work
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. For instance, it might be more productive to develop very fast treatment workflows without online adaptation to maximize patient throughput on an expensive proton therapy machine, instead of performing
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. This PhD will focus on uncertainty-aware machine learning models, developing and evaluating techniques (e.g., Bayesian and interval neural networks) to quantify model uncertainty and monitor it during