Sort by
Refine Your Search
-
(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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
workshops using approved trauma-informed methods; translate co-design evidence into requirements for a Tigrigna, offline-first/shared-device toolkit; contribute hands-on research and technical work in
-
, 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