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classification Estimation of the probability of developing diseases Anomaly detection Early diagnosis. The recipient will learn and apply a vast portfolio of complementary and synergic methods at the intersection
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possibility of extension) Start date: August 2026 at latest The students will be enrolled in the structured PhD programme in Computer Science at Sapienza University of Rome, Italy: https://www.uniroma1.it/en
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the Department of Mathematics & Statistics (https://www.reading.ac.uk/maths-and-stats/ ) About the project/work tasks: This position is part of: 19 PhD Fellowships available in Digital Endocrinology in the Marie
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mathematics, data and computer sciences, and biomedical engineering. The PhD candidate will be based at the Department of Mathematics & Statistics (https://www.reading.ac.uk/maths-and-stats/), which has a long
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estimation, and learning-based prediction models that anticipate the future motion of vessels seen in the radar data, based on the radar data, local geography and historical patterns. The methods
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. The objective of this PhD project is to develop learning-based methods for maritime tracking and prediction in time- and safety-critical applications. Artificial intelligence techniques will be utilized in order
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of current work processes. The project will adopt social science and sociotechnical perspectives such as computer supported collaborative work, HCI or organizational sociology to investigate the intra- and
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engines, and reinforcement learning—can be adapted and extended for maritime design challenges. Research areas will cover some of the following themes: Generative methods for design documentation, including
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state estimation and bias correction under uncertain sensing conditions. The PhD candidate will be supervised by Professor Thor I. Fossen, with Assoc. Professor Erlend M. Lervik Coates as co-supervisor
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@nmbu.no Terje Gobakken Professor +47 41512806 terje.gobakken@nmbu.no Where to apply Website https://universitypositions.eu/jobs/168966372-phd-scholarship-methods-for-chara… Requirements Research