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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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interpretable models that connect molecular patterns across multiple scales of human biology. The project lies at the interface of artificial intelligence, computational biology, systems medicine, and precision
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, mathematical modeling and statistics, or equivalent. We are looking for candidates with: A solid academic background with thorough computational and analytical understanding; Proficiency in programming in Python
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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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, animals, fungi, bacteria, etc.). The Program for Plant Ecology and Evolution, where this position is located, is home to eight research group focusing on genomics, adaptation and speciation as well
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will work closely with the group of Prof. Arne Elofsson at Stockholm University, who provides expertise in computational structural biology, protein modeling, and machine learning. The project therefore
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Development Design new statistical and machine learning models tailored to this emerging omics modality. Multimodal Data Analysis Work with high-dimensional datasets combining quantitative RNA features
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effects. Importantly, computational predictions will be directly linked to experimental evaluation of GalNAc-conjugated RNA therapeutics. This position offers a unique opportunity to work in a highly
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experimental and computational methods to identify molecular mechanisms leading to dysfunctional cellular states in human disease (www.camunaslab.org ). The candidate will contribute to the improve Slice-seq, a
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, or a related field, who enjoys interdisciplinary work spanning wet-lab experimentation and computational data analysis. In addition to the aforementioned requirements for the position: A Master’s