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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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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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some of the following skills: Localization and sensor fusion: Solid understanding of localization techniques and sensor integration. Experience with SLAM algorithms (vision-, acoustic-, or inertial-based
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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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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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, algorithmic, and real-time implementation framework for on-the-fly autonomy in crowds. The resulting methods will (i) adapt to unpredictable human interactions that introduce high levels of uncertainty, (ii
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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