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on principles from engineering, cognitive neuroscience, artificial intelligence, and human-computer interaction. It has potential applications in education, training, and cognitive rehabilitation, and contributes
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must have (or will receive in a few months) a Master’s degree in Computer Science Engineering, Master of Science in Information Engineering Technology, Master of Science in Computer Science, Master of
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. Digital Extraction from Historical Taxonomic Literature Application of OCR and machine learning algorithms to digitize printed and handwritten documents; Linking specimen mentions in literature to digital
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full-time to start the program in September 2025. Desirable: Dutch language proficiency Eligibility Conditions: Applicants do not already hold a doctoral degree. Applicants must not have resided
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Job description This PhD student position is focused on the impact of alphaherpesvirus infection on gap junction (GJ) permeability. Gap junctions are crucial communication channels. As one of their many functions, they allow virus-infected cells to warn neighboring cells about the imminent viral...
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will be part of the Scandinavian section of the Department of linguistics, which is responsible for teaching Swedish courses at the bachelor’s and master’s program at the department. You will work under
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. Louise Terryn. Job profile MSc degree (or equivalent) in a relevant field (Bio-Engineering, Forestry, Remote Sensing, Surveying, Physics, Geosciences, Environmental Sciences, Computer Science A passion for
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, computer science or quantitative criminology; The diploma requirements must be met by the time of appointment. • Intermediate programming skills (e.g., Python or R), as well as a willingness to develop these further
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the doctoral training program and other PhD courses; write and publish scientific articles related to your research project; present the data at scientific conferences. WHAT WE CAN OFFER YOU We offer a full-time
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learning algorithms. The two PhD students hired through this vacancy will primarily contribute to the development of debiased learning methods and assumption-lean modeling tools, and their application