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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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supervising PhD students and other team members. You will fulfil a limited number of teaching activities in the Master’s program in International Relations and Diplomacy. You will participate in the provision
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. Applicants should demonstrate expertise in programming languages such as Python and/or R, as well as experience working with high-performance computing clusters. The successful candidate will be a team player
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/programmes/all-programmes/master-film-studies-visual-culture/study-programme/ You will work as media and project manager for the ERC project, https://www.uantwerpen.be/en/projects/reworkchange/ (10% FTE) You
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possession), a motivation letter and two (email) addresses of potential referees to robrecht.raedt@ugent.be . Please mention “PostDoc application ” in the subject line. We do not accept late applications
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. Applicants should demonstrate expertise in programming languages such as Python and/or R, as well as experience working with high-performance computing clusters. The successful candidate will be a team player
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with (iPSC) tissue culture, neurodegenerative diseases or neuroscience, FLIM microscopy and organoids is a competitive advantage. You have (basic) bio-informatics skills or are willing to learn. Prior
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, and brain computer interface tasks. This project will support our goal of testing the Controllosphere Theory of cognitive effort (see doi 10.1037/rev0000467). A Ph.D. and background in computational
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the Controllosphere Theory of cognitive effort (see doi 10.1037/rev0000467). A Ph.D. and background in computational modeling, engineering or a related discipline is required; expertise with linear control theory and
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with (iPSC) tissue culture, neurodegenerative diseases or neuroscience, FLIM microscopy and organoids is a competitive advantage. You have (basic) bio-informatics skills or are willing to learn. Prior