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of computer vision algorithms, with a focus on assessing performance in edge deployment settings. Their role will involve supporting model development, running experiments, and analyzing results to evaluate
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algorithms for anomaly detection and predictive maintenance of subsea structures Duration: 6 months Maximum Duration Including Renewals: 12 months Objectives Development of AI-driven models to identify
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of parameters of the system using machine learning and artificial intelligence algorithms. - Assist the IST research team in the preparation of technical reports, presentations, and meetings, as
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that combine parallel architectures (i.e., GPUs or accelerator boards, clusters) and numerical algorithms suited to such architectures with the goal of improving the speed of convergence and the stability
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on application logic rather than underlying algorithm development), and the capability of independently driving the full "Data-AI-Deployment" process; (c) the ability to evaluate the fit between AI applications
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Bayes' theorem, sampling, cross-entropy loss), computational complexity & automata theory (including advanced algorithms, formal methods), and foundations of machine learning (including linear algebra and
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of Vienna). About the position: Lead the research group focusing on hybrid quantum algorithms, quantum neuromorphic computing, and quantum machine learning Build your own team (PhD students, postdocs) 4-year
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typically require stable quantum bits with long coherence times, this research proposes innovative programmable algorithms that can harness the power of imperfect quantum simulators to tackle complex
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Science at Queen Mary University of London, working with Professor Rachel Humphris and Dr Dimitrios Kollias. The successful applicant will undertake computational research, including algorithmic auditing
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relevant research or working experience in LLM/VLM and AI decision-making algorithms for end-to-end autonomous driving will be preferred. Good communications skills and the ability to work independently and