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Join MultiD Analyses AB and the University of Gothenburg to develop innovative bioinformatics and machine learning methods for RNA Fragmentomics, with the ambition to improve cancer care through
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cellular processes to human health and global ecosystems. The SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS) aims to recruit and train the next generation of data-driven life
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School of Engineering Sciences in Chemistry, Biotechnology and Health at KTH Project description Third-cycle subject: Biotechnology The project aims to develop probabilistic deep learning models
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cold solid tumors, remain resistant to current immunotherapies. A major goal in the field is therefore to develop new strategies that increase tumor immunogenicity and improve anti-tumor immune responses
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Umeå University, Faculty Office of Medicine Umeå University is one of Sweden’s largest higher education institutions with over 41,500 students and about 4,600 employees. The University offers a
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students, and administrative staff. Research and education at the department occurs in an international environment and is focused on animal biology. Outstanding and high impact research is conducted in a
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contribute new and better ways to analyse and interpret large-scale data. In your position, you will develop computational methods for cryo-EM reconstruction, heterogeneity analysis, and modeling of structural
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School of Engineering Sciences in Chemistry, Biotechnology and Health at KTH Job description The Affinity Proteomics unit (https://www.scilifelab.se/facilities/affinity-proteomics/ ) is part of
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evolution across different genomic regions by developing interpretable and efficient methods in comparative pangenomics, leveraging machine learning methods and statistical analysis (https://cgrlab.github.io
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to human health and global ecosystems. The SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS), coordinated by SciLifeLab, aims to recruit and train the next-generation of data