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Field
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responsible for the end-to-end investigation of novel federated learning strategies for causal inference. The role will bridge rigorous theoretical work with hands-on algorithm design and development on real
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an opportunity for a Research Associate to develop quantum-enabled synchronisation algorithms for deployment on space-based platforms. You will contribute to research involving quantum and classical optical
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of predictive models, multimodal data integration, development of explainable AI algorithms, analysis of clinical, biological and imaging data, and implementation of software tools supporting biomedical research
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C++ techniques. Solid understanding of algorithms, data structures, and memory management. Familiarity with debugging tools and performance profiling. Experience with version control (Git
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of the ASSET Junior Professor Chair (Tenure Track Professor) will be responsible for developing and structuring a research programme of excellence at the interface of advanced algorithmics, embedded systems
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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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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