115 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "The Institute for Data" positions at Ghent University
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: https://arxiv.org/abs/2508.06112 What we are looking for: You have a Master degree that implies a profound knowledge of statistics, data analysis and scientific programming. You have affinity with
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efforts acquire a particular urgency. Documentation provides evidence for accountability while simultaneously advancing resistance against erasure and denialism. Palestinian documentation practices can be
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an integrated research approach that supports mutual learning, forward thinking, and co-creation within the team. This is not an individual PhD project. There is a set research agenda and pre-established research
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to contribute their expertise, experience and interests, while jointly shaping an integrated research approach that supports mutual learning, forward thinking, participatory research practices. Please consider
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physical principles into the learning process to maintain physical consistency outside the training domain. This PhD research is envisioned to result in a breakthrough in the application of machine learning
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professors, 2 postdoc researchers, and about 20 PhD students. The research for these PhD positions will be conducted in the System Software team, headed by prof. Bjorn De Sutter (https://users.elis.ugent.be
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within the CVAMO Flanders Make Lab at Ghent University. The project focuses on developing machine learning models to predict manufacturability and manufacturing effort directly from CAD geometry
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vision models for automated performance assessment and feedback. Ultimately, this research will contribute to the creation of scalable, data-driven training programs that enhance surgical performance
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European cities. The project explicitly embraces a broad AI perspective, including (but not limited to): machine learning and statistical learning computer vision and sensor-based data analysis natural
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, incorporating transient tribological changes. Creating machine-learning-based surrogate models to enable rapid efficiency and lifetime predictions under realistic operating conditions. Validating the developed