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Field
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with process safety and security concepts, accident modelling approach, and dynamic Bayesian Networks would be advantageous. Willingness to conduct research in a multi-national project team. Fluent in
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under varying lighting, fabric blends, and soiling; (5) porting the inference pipeline to an embedded/edge-compute platform; (6) integrating with our robotic pick-and-place cell for iterative field trials
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creative – You bring substantial knowledge of statistical (e.g. Bayesian) methods, strong analytical skills, and creativity. Programming skills – You are proficient in Python and/or Matlab. Research
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the inside out. Your role: Develop experimental approaches for imaging-based characterization of soft matter. Apply and advance continuum mechanics and machine learning techniques to infer mechanical
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such networks and to unleash further features, in particular positioning, tracking mobile devices, and sensing. By addressing these research questions you contribute to making OWC technology mature for use in
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, readout, alignment, and data acquisition). For the phase-2 upgrade (2027-2030), we will instrument and commission one of the end-caps of a new all-silicon inner tracking system (ITk) in Amsterdam
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to electrochemisty and electromagnetics. Interface tracking/capturing methods such as immersed boundary method, level-set method, volume-of-fluid, phase filed method are options for model development.
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implement a tree-level fire experiment in dry and wet forest in Bolivia. For a set of 10 tree species per forest type, the PhD will implement different fire intensity and frequency treatments while tracking
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. Stef van den Elzen and dr. Fernando Paulovich. The visualization cluster (https://research.tue.nl/en/organisations/visualization-3 ) at TU/e has a strong track record in visualization and visual
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-oriented solutions, and the advancement of knowledge. The first sub-project; a PhD track, focusses on the characteristics of transformative competencies to be achieved as learning outcomes, and pathways