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eSSENCE graduate school in data-intensive science. The school addresses the challenge of data-intensive science both from the foundational methodological perspective and from the perspective of data-driven
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group develops theory, methods and software for data-driven science, with a current focus on uncertainty quantification in large pre-trained models (vision-language models), generative models (flow
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description Quantitative analysis of lipid nanoparticles (LNPs) using Cryo EM is challenging due to heterogenous samples, lack of training data and sample variability. In this project we aim to develop AI
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September 30, 2026 Read more and apply SciLifeLab / Careers / Postdoc in Bioinformatics and Machine Learning Are you excited about research at the intersection of genomics and data science? We are