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learning. Your job In the ERC project FoRECAST, we aim to develop theory (e.g., new probabilistic and differential inference algorithms as well as proofs of their correctness and efficiency) and systems (e.g
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to the research; Good understanding of computer architecture; Basic understanding of MRI algorithms is a plus; Understanding of AI and its practical implementations; The ability to work in a team and take
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algorithms that align prefab factory production schedules with IWT capacity, terminals, and urban delivery windows. Model multi-level planning decisions, connecting early feasibility assessment and quotation
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planning, and explainable decision support. The PhD will operate across two worlds: The University of Twente — advancing scientific models, algorithms, and hybrid AI methodologies; Thales (the industrial
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responsibilities include: Development of a flood classification framework for flood type prediction Comparison of different ML algorithms in a sensitivity study Communication with stakeholders Development of open
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the upcoming flood type, e.g. heavy-rainfall flood or rain-on-snow flood. As PhD candidate you will compare several machine-learning based algorithms regarding their ability to predict the flood type based
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graph learning models, primarily geared towards assisting combinatorial solvers for practical graph algorithm benchmarks. Please find out more here: Dr. G. Rattan Your profile You have, or will shortly
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a primary emphasis on designing smart algorithms to trigger non-invasive blood pressure (NIBP) measurements at critical times. This will involve leveraging physiological sensor signals such as the
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to source localization based on microphone arrays or distributed sensors. This PhD project will focus on the development of novel methods and algorithms for airborne noise source localization in generic urban
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science and societal application. We contribute to innovative information technologies through the development and application of new concepts, theories, algorithms, and software methods. With our expertise