64 computer-science-intern-"https:"-"https:"-"https:"-"https:"-"Ulster-University" positions at Aarhus University
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and around 825 students are enrolled in our study programs. Furthermore, we also offer an ambitious PhD program. Our PhD students have high academic ambitions and deliver high-quality results for both
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cognitive science. We are looking for an applicant who can strengthen our research profile in computational modelling of cognitive processes and/or computational modelling of social processes. The ideal
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Communication and Culture (CC) and the Department of Computer Science (CS) at Aarhus University, cctd.au.dk. The place of employment is Department of Computer Science at Aarhus University (AU), and the project
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University also offers a Junior Researcher Development Programme targeted at career development for postdocs at AU. You can read more about it here . At the Faculty of Natural Science at Aarhus University, we
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or pharma science. Profile and competences The candidate is expected to build an independent research group and conduct an active research program, which is internationally recognized and can attract external
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., open calls for 'letters of interest'). Facilitate workshops focused on analyzing the need for local vs. subscription-based LLM services. Collaborate with computer science researchers on NLP and Knowledge
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Society at the Department of Food Science, Aarhus University ( http://food.au.dk/en/foodresearch/science-teams/food-quality-perception-society/ ). The position will be affiliated to science-based advice
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responsible for two educations: Molecular Biology and Molecular Medicine with a yearly uptake of 160 students in total. Please refer to http://mbg.au.dk/ for further information about The Department
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collaborate closely with internal and external partners to advance the project. Your profile The ideal candidate holds a PhD in biochemistry, structural biology or a related field, and has hands-on experience
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across molecular biology, ecology, bioinformatics, and environmental science. The taxonomic scope is broad and inclusive: we aim to collect comprehensive data across multiple taxonomic groups to support a