218 associate-professor-computer-"https:" "https:" "https:" "https:" uni jobs in Belgium
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? Send your CV, copy of your diploma and a motivation letter to Professor Bert Devriendt (b.devriendt@ugent.be ) before the 28th of February 2026. We advise to submit your application as soon as possible
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of the UNPACK team, you will be intensively working together in a team of 8 researchers and 4 professors. You will share your data and analyses with your co-researchers and supervisors, and engage in
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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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engineering, and have expertise in building camera systems and computer vision. This role also involves working closely with the other members of the team on projects related to plant phenotyping (assessing e.g
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working together in a team of 8 researchers and 4 professors. You will share your data and analyses with your co-researchers and supervisors, and engage in extensive collaborative (interdisciplinary
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database for construction products in service. The technology will enable accurate computation of the CO2 uptake of cement-based materials. It will support material modifications to boost CO2 uptake and
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-associated research lab Centre for Microsystems Technology (CMST) (Department of Electronics and Information Systems) and (b) Electrochemistry and Surface Analysis (ESA) (Department of Chemistry) at Ghent
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data center, compute, storage, networking, and core services Ensure high availability, performance, security, and compliance of infrastructure platforms Manage capacity planning, lifecycle management
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excellent study results. You are proficient in at least one programming language (e.g., python, c++, ...) Strong communication skills in English are essential. Knowledge of inverse problems, computational
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working on nonlinear and multiphoton optical spectroscopy and microscopy for molecular and materials characterization. The project is part of the broader MIP research programme across KU Leuven (Leuven and