13 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"U.S" positions at Ghent University in Belgium
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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
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to the Special Research Fund. Deadline Submissions are made via FWO. The deadline is 17 November 2025. Candidates who acquire a BOF fellowship in this call (2026) are required to submit a new application to the
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session (November 2022) to learn more about the financial, job-and HR-related aspects of your fellowship. More information See FWO website (FO and SB ) for detailed information on the call, (bench fee
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skills, and are interested in both wet-lab work and bioinformatics. Candidates should be motivated to acquire basic bio-informatic skills (R,…) as the technologies that will be used involve complex data
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to work in a multilingual environment. You are empathetic, work with precision, and have a critical mindset. You are open to giving and receiving constructive feedback, you value continuous learning. You
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contribute to a positive work atmosphere where continuous learning, development, and collaboration are paramount. Previous experience with working in interdisciplinary teams is a plus. You are stress-resistant
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. You can work autonomously as well as in a team. You contribute to a positive work atmosphere where continuous learning, development, and collaboration are paramount. You are stress-resistant and
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: it enables researchers to contribute their expertise, experience and interests, while jointly shaping an integrated research approach that supports mutual learning, forward thinking, participatory
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contribute to the development of models for electrical machines for sustainability. This project aims at developing smart parameterized multiphysics models for the electric machines. As a PhD student, you will
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clothing, such as for first responders and military, ergonomic and thermos physiological comfort are often jeopardized. The purpose of the research is to better understand how to improve the balance between