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Do you enjoy hands-on analytical chemistry and working with advanced mass spectrometry? At Chalmers Mass Spectrometry Infrastructure (CMSI), you will contribute to a wide range of life science
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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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application! We are looking for a PhD student in Medical Science, AI and Bioinformatics. Your work assignments This project aims to develop AI foundation models for integrative single-cell and multi-omics
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in large pre-trained models (vision-language models), generative models (flow matching, diffusion), simulation-based inference, and robust and active learning. The group has a wide network of
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islet physiology and single-cell genomics to join the lab of Dr. Joan Camuñas. The lab of Dr. Joan Camuñas stands at the interface of genomics, biophysics and precision medicine. Our mission is to develop
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. Simulation-based inference (SBI) addresses this by training neural networks, such as flow-matching generative models, on simulated events. The project aims to develop efficient, robust and calibrated SBI
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and variation. The successful candidate will develop innovative methods and models to advance our understanding of genome evolution and variation. The position is based in the Computational Genomics
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samples, lack of training data and sample variability. In this project we aim to develop AI/ML workflows for improved quantitative analysis of LNPs. Your responsibilities will include optimisation of data
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different professional and cultural backgrounds. The doctoral project aims to develop next generation minimally invasive sampling technologies for neuro biomarkers. The work includes developing the technical
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the MIDA – Methods for Image Data Analysis – research group at the Department of Information Technology, and will be conducted alongside other researchers at the Centre for Image Analysis who develop