166 machine-learning "https:" "https:" "https:" "https:" "The Open University" PhD positions in Denmark
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of machine learning Distributed and federated training The candidate is expected to hold a relevant MSc degree in Computer Science, Data Science, Physics, (Applied) Mathematics, Computational Statistics
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project’s principal investigator, Associate Professor Lars Rohwedder, an internationally recognized expert in the areas of approximation algorithms and parameterized algorithms, see https://larsrohwedder.com
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decision-making; and (iii) decision-support to compare trade-offs and policy alternatives. The position is supervised by Professor Francisco Pereira, with co-supervision from colleagues in machine learning
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, computer science, and computer engineering, including artificial intelligence (AI), machine learning, internet of things (IoT), chip design, cybersecurity, human-computer interaction, social networks
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with Robotics Excellent programmer in Java / C / Python / ROS or equivalent Excellent at using Machine Learning software, e.g. PyTorch / TensorFlow / Scikit Learn Highly knowledgeable in mathematical
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employees and 10 research sections. We broadly cover digital technologies within mathematics, data science, computer science, and computer engineering, including artificial intelligence (AI), machine learning
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digital technologies within mathematics, data science, computer science, and computer engineering, including artificial intelligence (AI), machine learning, internet of things (IoT), chip design
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candidate is expected to hold: A master degree in biomedical engineering or computer science, Excellent programming skills (Python). Experience with data curation, large-scale datasets, and machine learning
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. You will also spend 3 months at Georgia Tech/Emory University (USA), working on machine learning and data benchmarking. Work description The selected PhD student will be responsible for the full
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, sensing at the robot–environment interface, and bioinspired control strategies to allow the robot to perceive and adapt to different terrains. By bridging soft robotics, physical intelligence, and learning