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approach could resolve this issue and we could use obtain data-driven models using machine learning algorithms such as artificial neural networks, reinforcement learning, and deep learning. A typical caveat
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to test data, which are therefore only useable within a narrow range of scenarios. These limitations result in the requirement of large number of high-cost experiments being conducted to populate the models
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and has a large group of collaborators. You will be joining a great team of supportive and social PhD students working in a high-quality research environment. Learn More: The Dynamics Research Group
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We are looking for a doctoral candidate with a strong computational, engineering, data scientific or machine learning background that is keen to work in an interdisciplinary environment and open to
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Vehicles (UAVs/USVs), and to harness this imagery to characterise the surroundings of a sea vessel. Such systems will comprise both hardware and signal processing approaches to acquire data and obtain high
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multimodal machine learning, large language models, and fairness and uncertainty evaluations. The PhD student will benefit from: State-of-the-art AI computing recourses for large-scale model training including
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networks, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our
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Institute). Qualifications We seek excellent students with a strong background in cosmology, astrophysics, physics, mathematics and/or computer sciences, who seek to obtain a Joint-PhD degree from
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-theory, machine learning, coding skills, theoretical solid mechanics, numerical analysis. The official transcripts of your BSc and MSc grades List of at least two references with full contact information
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of the top tier dynamics groups in the World with 15 academic staff and over 50 PhD students. The Group covers a wide range of fundamental and applied research and has a large group of collaborators. You will