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graph based machine learning for discrete and continuous structures, led by Frank Drewes, Johanna Björklund, and Henrik Björklund. The PhD student will work within the context of the STING (Synthesis and
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machine learning and in mathematical/logical problem formulation (e.g. optimization, game theory, graph theory). About the position The position provides you with the opportunity to pursue PhD studies in
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26th 2024. Project description and tasks Machine learning (‘artificial intelligence’) is having an immense impact on both society at large and research especially, and this impact is expected to increase
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problem or what heuristics organisms might evolve. This research project is a collaboration between Eric Libby and Laura Carroll. It involves using machine learning techniques to infer the mechanisms by
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of topics in modern machine learning research, including geometric deep learning, non-convex optimization problems and federated learning. In addition, this project is deeply connected with
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etc.) Automated reasoning Machine learning Candidates are expected to have good knowledge in Artificial Intelligence and good programming skills in some of the following: Python, PyTorch library, OpenAI
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will be predominantly conducted in English. Experience in broad areas of expertise, including machine learning algorithm development, statistical methods, distributed learning, and cybersecurity, is
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the development of new techniques for rehabilitation and functional impairments of injuries to the upper extremity supported by machine learning and neural networks. The position is an initiative within