54 assistant-professor-computer-"https:" "https:" "https:" "https:" "EURAXESS" positions at Linköping University
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media and visual communication. The research ranges from foundational computer graphics and visualization technology to applications in areas such as medicine, astronomy, and biology. An emerging research
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benefits is available here . Union representatives Information about union representatives, see Help for applicants . Application procedure Apply for the position by clicking the “Apply” button. Your
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NAISS, the National Academic Infrastructure for Supercomputing in Sweden, provides academic users with high-performance computing resources, storage capacity, and data services. NAISS is hosted by
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, genetic manipulations, analysis of genomic rearrangements, telomere assays, and RNA sequencing. The activities include literature review, lab working and computational bioinformatics analysis. Your
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induction. You will combine advanced genetic engineering approaches with survival assays, fluorescence-based techniques in fixed and live cells, single-cell sequencing, and computational bioinformatics
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or data science, with suitable specialization, in medical physics with a sufficient portion of mathematics included, or other related scientific areas. You have good skills in computer programming. A strong
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media and internet infrastructure computing cultures and materialities as heritage values and economies in algorithmic/data cultures social and cultural perspectives on dismantling communication networks
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statistics and machine-learning–assisted approaches, in close interaction with data science collaborators Active collaboration across disciplines spanning spectroscopy, soft matter and nanomaterials
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visualization. Do you want to help shape the future of education? Your work assignments The advertised position is part of a Marcus and Amalia Wallenberg (MAW) foundation funded project that investigates
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, where AI models are trained without having all data in a single computer. This makes it possible to use larger datasets for training, without sending sensitive data between hospitals. The goal is to