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Uppsala University, Department of Information Technology Are you interested in probability theory, statistics, and mathematical modelling? Would you like to develop new methods for uncertainty
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research environments in Computational Science, the research and education has a unique breadth, with large activities in areas such as numerical analysis, mathematical modelling, development and analysis
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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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Are you interested in developing mathematically grounded methods for uncertainty quantification in deep learning, particularly for large language models in healthcare applications? Are you looking
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computer science, image analysis and machine learning, engineering physics, data science, applied mathematics, molecular biotechnology engineering, or another related field; or Have completed at least 240
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Uppsala University, Disciplinary Domain of Science and Technology, Faculty of Mathematics and Computer Science, Department of Information Technology Are you interested in working with probabilistic
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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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predictive deep learning models, and physical mechanistic models (thermodynamic and kinetic models etc.). Examples of suitable backgrounds: machine learning, programming, mathematics, physics. You will
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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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requirements, the applicant must have credits in Life Science, Computer Science Mathematics, Physics or Bioinformatics or alike, including a 30 credit Degree Project (thesis). proficiency in English equivalent