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limited to, deep reinforcement learning, federated learning, deep learning and meta learning. The overall aim is to improve the efficiency in cyber-physical systems, such as drone swarms, that support 5G
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of computer science, artificial intelligence, and biomedical research. Your profile Master's degree in computer science or related discipline Experience with Python and recent deep learning frameworks (e.g. Pytorch
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Science. Commitment to undergraduate and graduate education. Demonstrated expertise in machine learning/deep learning and software development (Python; PyTorch/TensorFlow). Peer-reviewed publications and strong
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that shape our future. Fueled by curiosity and a deep sense of duty, they contribute invaluable insights to research and teaching, enriching our society. Are you inspired and driven by the desire to make a
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areas, could include deep learning (e.g. Long Short Term Memory - LSTM), statistical baselines (e.g. Autoregressive Integrated Moving Average - ARIMA, Kalman filters) and transformers (e.g., spatio
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future. Fueled by curiosity and a deep sense of duty, they contribute invaluable insights to research and teaching, enriching our society. Are you inspired and driven by the desire to make a meaningful
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higher degree students. What we’re looking for: A postgraduate qualification (Masters, PhD or equivalent) in a relevant field. Experience in University-level teaching and learning. Clinical/industry
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competencies Education You should have completed within the past five years or be close to completing a PhD in a relevant field such as data science, AI, computer science, machine learning, Earth system science
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learning , AI for Health Skills : Knowledge : Where to apply Website https://rubis.univ-spn.fr/offres/voir/195 Requirements Specific Requirements Master 2 en science des données Additional Information Work
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artificial intelligence (i.e. machine, deep and reinforcement learning…) to optimize efficiency, improve safety, reduce costs and promote sustainability. Collaborate with multidisciplinary teams to uncover a