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Join ABC Labs and KTH as an Industrial PhD Student to build data-driven models of human biology with multimodal health data — interdisciplinary impact, real-world healthcare. About the role We
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. Project description Data-driven mathematical and statistical models are increasingly used in life science research and healthcare. Quantifying the uncertainty associated with these models is crucial
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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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machine learning for the next generation of AI models – uncertainty-aware foundation models, generative models and world models – with the support of competent and friendly colleagues in an international
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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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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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offers a unique interdisciplinary training environment bridging experimental mass spectrometry-based proteomics and AI-driven protein structure modeling. The student will have access to existing large
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expertise. Are scientifically curious, independently driven, and motivated by biologically meaningful modelling problems. Have good teaching abilities. Have awareness of diversity and equal opportunity issues
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and biophysics, at Stockholm university. For more information about us, please visit: www.dbb.su.se . Main responsibilities At the SciLifeLab and Wallenberg National Program for Data-Driven Life Science
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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