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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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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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of algorithms, machine learning, optimization, scientific software development and high-performance computing. The division is also an important part of the eSSENCE strategic collaboration on e-science and of
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of the world’s largest research environments in computational science, with large activities in areas such as machine learning, optimization, scientific software development and high-performance computing
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postdoctoral in Biological Data Systems to develop scalable data infrastructure and computational systems for large biological datasets. The position will be embedded within the Human Protein Atlas at KTH and
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on development of novel computational methods with state-of-the-art machine learning for gaining fundamental insights into healthy and diseased human tissues of the heart, cardiovascular system, and
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division The Division of Biomedical Engineering is part of the Department of Materials Science, and Engineering at the Ångström Laboratory. We perform research within the development of miniaturized
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constellation of SciLifeLab researchers and infrastructure units. This position is embedded in Avlant Nilsson’s research group at Karolinska Institutet and SciLifeLab. Our lab develops deep learning models
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technical university, we play an active role in advancing the transition towards a sustainable society. At KTH, you have the opportunity to grow and develop in a creative and dynamic environment, with good