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- Delft University of Technology (TU Delft)
- Delft University of Technology (TU Delft); yesterday published
- Delft University of Technology (TU Delft); 17 Oct ’25 published
- University of Twente
- University of Twente (UT)
- Wageningen University & Research
- Delft University of Technology (TU Delft); Published yesterday
- Delft University of Technology (TU Delft); today published
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Field
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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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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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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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Plan programme, aimed as a flagship project for changing planning and scheduling in high mix low volume (HMLV) production by leveraging hybrid AI, data-driven workload estimation, intelligent release
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-to-end planning, connecting prefab factory production schedules with urban construction projects through an AI-driven decision-support system that synchronises production planning, IWT capacity, terminal
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industrial doctorate position is part of the Predictive Plan programme, aimed as a flagship project for changing planning and scheduling in high mix low volume (HMLV) production by leveraging hybrid AI, data
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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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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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to surveillance of infectious pathogens using computer science and mathematics? Join the Delft Bioinformatics Lab and work on graph-based algorithms for microbial genomics! Job description Bacterial and viral
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Do you want to contribute to surveillance of infectious pathogens using computer science and mathematics? Join the Delft Bioinformatics Lab and work on graph-based algorithms for microbial genomics