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of Ghent University (http://www.ugent.be/en ) and Ghent University Global Campus (http://ghent.ac.kr/ | http://www.ugent.be/globalcampus/en ) to learn more about our organizations. Center forBiosystems
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applications for the position of Professor (W3) for effective teaching and learning in subject didactics (f/m/d) to commence as soon as possible. The professorship is intended to advance internationally visible
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) Positions PhD Positions Application Deadline 20 Apr 2026 - 18:00 (Europe/Prague) Country Czech Republic Type of Contract Temporary Job Status Full-time Hours Per Week 40 Offer Starting Date 1 Jun 2026 Is the
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positioning of results for partnerships, licensing, or venture creation. Your profile PhD (or equivalent experience) in Computational Biology, Bioinformatics, Systems Biology, Machine Learning, or a related
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dedicated candidate who is expected to Initiate, conduct and lead research in clinical child, adolescent, and/or family psychology Teach topics related to clinical work with children, adolescents, and
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, there are about 21 academic and teaching staff and 13 Research Assistant Professors in the Department. Please visit the website at http://www.polyu.edu.hk/fsn/ for more information about the Department. The Hong
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@sheffield.ac.uk or look at the University’s website: https://www.sheffield.ac.uk/postgraduate/phd. Further Information on the Particle Physics group in Sheffield and our projects can be found here: https
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positioning of results for partnerships, licensing, or venture creation. Your profile PhD (or equivalent experience) in Computational Biology, Bioinformatics, Systems Biology, Machine Learning, or a related
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(PhD preferred) in a field with relevance to physical therapy, with the ability to teach basic and clinical sciences. Position responsibilities will include teaching within the highly collaborative
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position as Senior Lecturer. Optimization, machine learning, and control theory together form a central toolbox for understanding, analyzing, and controlling complex systems. These fields span deep