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of algorithms based on artificial intelligence, since, to fully exploit the potential of AI, algorithms must be fed with data. This research project will examine these issues by focusing on three main areas
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, and systematic evaluation of results. Objectives: Development and application of artificial intelligence algorithms for different use cases in the energy sector, e.g., forecasting of renewable energy
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workflows into structured representations suitable for AI planning and optimization algorithms. 2) Research Leadership & Mentorship: * Abstract from the practical challenges presented by the work and
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persist across participants, and retraining from scratch is often computationally infeasible at scale. In this project, you will develop the next generation of federated machine unlearning algorithms
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successful candidate is required to: • Contribute to Robust Splatting, Dialogue, Speech Signal Processing and Machine Learning algorithms. • Contribute to Image Processing and Machine Learning algorithms
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on research topics related to AI in Education. We are looking for a candidate with prior research experience in both AI models/algorithms and learning sciences/education background. This will help in
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it is to be expected that the environment contains obstacles or is partitioned in a way not apparent when starting the coverage plan. Classic “Coverage Path Planning” algorithms are restricted in
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. The successful candidate will assist in developing novel algorithms and integrating them into robotic platforms, helping to push the boundaries of embodied intelligence in both research and practical deployment
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candidate to develop and evaluate a mathematical model and algorithm to better tailor (risk-based) follow-up after cancer treatment. The role is highly impactful for ensuring sustainable cancer care in
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demonstrations. The successful candidate will work at the intersection of multi-disciplinary modelling, advanced AI algorithms, and decision-support tool development. Responsibilities will include programming