17 cloud-computing-"https:" "https:" "https:" "https:" "https:" "https:" "St" "St" "St" PhD positions at Linköping University in Sweden
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application! We invite applications for a fully funded PhD student position to join the research group of Andrew Winters to work on challenging problems in Computational Mathematics for accurate and reliable
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=sv 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 https://liu.se/en
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application! We are looking for a PhD student in Statistics and Machine Learning Your work assignments We are looking for a PhD candidate to work in the intersection of computational statistics and machine
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competitive advantage (https://liu.se/en/research/cbmi ). You will work under the supervision of Professors Christian Kowalkowski and Daniel Kindström. Research at IEI spans a broad range of areas, from
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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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), Institutionen för Biomedicinska och Kliniska vetenskaper (BKV ). The employment When taking up the post, you will be admitted to the program for doctoral studies. More information about the doctoral studies
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application! We are looking for a PhD student in Statistics with placement at the Division of Statistics and Machine Learning, Department of Computer and Information Science. Your work assignments As a PhD
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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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different backgrounds. This position requires that you have graduated at Master’s level in in computer science, media technology, computer engineering, human-computer interaction, visual learning and
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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