15 post-doc-image-engineering-computer-vision "NTNU Norwegian University of Science and Technology" PhD positions at Linköping University in Sweden
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engineering as well as knowledge graphs, and graph data. The employment When taking up the post, you will be admitted to the program for doctoral studies More information about the doctoral studies at each
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at the Department of Computer and Information Science will focus on the usability and interaction with semantic technologies. Based on the semantic web technology stack for implementing DPPs, and an ontology-based
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educational technology on learning in public educational spaces. You are expected to produce research outputs relevant to the fields of visual learning and communication, and computer science. These outputs
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/research/laboratory-of-organic-electronics/research . The employment When taking up the post, you will be admitted to the program for doctoral studies. More information about the doctoral studies at each
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training programme complementing scientific skills with personal and entrepreneurial skills, including communication to various audiences, career development, intellectual property and startup-funding
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application! We are looking for up to two PhD students in trustworthy machine learning, with a particular focus on cybersecurity, privacy, and verifiability for AI systems, based at the Department of Computer
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to Human sequences and viceversa - Experience in Culturing Dictyostelium discoideum - Experience in Genetic engineering and developing CRISPR constructs - Experience in Bioinformatics and data analysis
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-supervision from Professor Fredrik Tufvesson. The employment When taking up the post, you will be admitted to the program for doctoral studies. More information about the doctoral studies at each faculty is
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to this collaboration. The employment When taking up the post, you will be admitted to the program for doctoral studies. More information about the doctoral studies at each faculty is available at Doctoral studies
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cross-disciplinary research initiative involving both computer and material scientists, providing excellent opportunities for practical impact by taking the outputs from the developed machine learning