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School of Engineering Sciences in Chemistry, Biotechnology and Health at KTH Job description Quantitative analysis of lipid nanoparticles (LNPs) using Cryo EM is challenging due to heterogenous
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regions by developing interpretable and efficient methods in comparative pangenomics, leveraging machine learning methods, statistical analysis and efficient algorithm and data structures (https
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development, high-throughput data analysis, and working with large population-based cohorts and clinical biobanks. The student will learn how to scientifically assess the study quality, perform appropriate
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Metabolomics and Exposomics Platform within SciLifeLab. You will join a team with complementary expertise in analytical chemistry, mass spectrometry, metabolomics and data analysis. You will conllaborate with
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for studying binding and dynamical structure of DNA, RNA and proteins. Scientific questions in projects can involve, for example, studying specificity in transcription factor – DNA binding, detecting protein
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analysis to better understand how molecular and cellular processes are coordinated across cells, tissues, and organ systems in human health and disease. You will be responsible for developing and applying
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Uppsala University, Department of Information Technology Are you interested in developing new image analysis and machine learning methods for precision medicine and clinical decision support? Would
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experience in population genomic modeling (e.g., using SLiM), analysis of structral variants from long‑read data, population genomic analysis of whole‑genome re-sequencing data are a merit — these techniques
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Umeå Plant Science Centre (UPSC) The Department of Plant Physiology is offering a postdoctoral scholarship within the project Con-TEki, which investigates the role of transposable elements (TEs) as
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of cohort analysis, prediction modelling, or machine learning techniques • Good knowledge about pancreatic cancer epidemiology • Excel in R or SAS • Good publication records Priority will be given