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(for steam production), (optimal) control (MPC), physics-based modelling and optimization. Numerical optimization, scientific computing (in C/C++) and general coding (python, Java) are important
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interpretability and data adaptivity. Operator inference strategies can/will be employed to infer the properties of such a model. • Extend the methods to a parametric calibration model through new material
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trustworthy AI methods tailored to ILC. The PhD researcher will fine-tune and benchmark pathology foundation models using multi-site H&E and immunohistochemistry whole-slide images. The aim is to learn
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effects throughout the exposure process.The research is primarily quantitative and uses advanced analytical methods. Longitudinal data are already available, enabling you to start developing your first
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version control (Git) and DevOps tools (Docker, Kubernetes, CI/CD pipelines). Familiarity with high-performance computing (GPU, CUDA, Slurm, etc.). Notions of full-stack software development or a
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controlled lab settings (drone cage, motion capture, hardware-in-the-loop simulation, onboard computing) and in outdoor flight campaigns, with application domains including long-range infrastructure
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autonomous bus currently operating in Leuven. You will develop innovative methods to design and evaluate driving strategies that make automated systems better “team players” in traffic, while also
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, database theory, and edge and cloud computing, this research will pave the way for a new reasoning paradigm that unites the expressiveness of materialisation with the efficiency of virtualisation. You
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and turned into insight). To tackle this, the research blends ideas from knowledge graphs, stream processing, database theory, logic, edge and cloud computing, and Artificial Intelligence into a
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survey and longitudinal analyses, the PhD project may, for example, make use of ethnographic methods, digital ethnography, observations, interviews, diary studies or other digital methods to gain