57 genetic-algorithm-computer-"Washington-University-in-St" positions at SciLifeLab in Sweden
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maintenance of instruments and computer systems, as well as assisting researchers in preparation of EM samples, data collection, and image analysis. You will also act as a coordinator for ongoing facility
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gene editing, dynamic enzyme regulation, as well as screening of genetic libraries. The project will also make use of systems biology data, such as genomics and proteomics, to achieve these goals
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research school. Data driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular
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administrative support systems Solid computer skills and proficiency in Microsoft Office (including Excel), and the ability to adopt new digital tools is required. Fluency to express yourself in speech and writing
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Are you passionate about applying computational approaches to solve problems in biomedicine? We are now looking for an Industrial PhD student in Data-Driven Life Sciences to work on a cutting-edge
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, molecular biology, computer science or related subjects the employer considers of relevance to the position Experience (3+ years) in working with advanced bioinformatics analyses of omics data from high
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other experts within the Support for Computational Resources unit at NBIS and related organisations, notably SciLifeLab, National Academic Infrastructure for Supercomputing in Sweden (NAISS), and EuroHPC
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National Program for Data-Driven Life Science (DDLS) is a 12-year initiative that focuses on data-driven research, to train and recruit the next generation of life scientists and create strong and globally
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course catalog and you will have the opportunity to participate in teaching at advanced level (PhD level and up). Requirements PhD in Bioinformatics, Computational Biology, Computer Science, or a related
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at least 1 million DNA barcodes. The project involves collaboration with a computer vision lab at Linköping University, focused on developing AI-assisted techniques for picking out specimens for genome