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candidate will join the Scientific Machine Learning group at TDB and SciLifeLab. The group develops theory, methods and software for data-driven science, with a current focus on uncertainty quantification
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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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Umeå Plant Science Centre (UPSC) The Department of Plant Physiology is offering a postdoctoral scholarship within the project Con-TEki, which investigates the role of transposable elements (TEs) as
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Machine Learning group at TDB and SciLifeLab (Associate Professor Prashant Singh), which develops methods and software for simulation-based inference, generative models and robust machine learning, together
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methods are developed in parallel, the postdoc will develop systems and services that make biological data accessible to AI and computational tools, collaborating closely with the Human Protein Atlas (HPA
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of the position is method development. We are seeking a postdoctoral researcher to develop next-generation AI models of cellular dynamics, with a focus on scalable neural network architectures that represent
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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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leading the investigation of structural and biophysical properties of miniaturized tumor environment models. A multidisciplinary approach is expected, integrating microfabrication, cell component and