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of Molecular Mechanisms and Machines, (IMOL), Poland, and the Leicester Institute of Structural and Chemical Biology, United Kingdom. For more information about the total announced post-doctoral positions within
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experimental and computational tools, and are currently recruiting for the following roles: Position 1: AI and data science approaches applied to genomics and spatial omics Position 2: Experimental islet and
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. The research group is part of the National Program for Data-driven Life Science (DDLS), generously funded by the Knut and Alice Wallenberg Foundation: www.scilifelab.se/data-driven/ Our group focuses on studying
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. The applicant should be proficient in written and spoken English, and have good computer skills (e.g Word, Photoshop, BioRender, Excel). Also, it is important that the candidate demonstrates independence, as
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, computational materials science, computer science, or a related field, awarded no more than three years prior to the application deadline*. Background in physics-based battery modelling and/or machine learning is
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at least 1 million DNA barcodes. The project involves collaboration with a computer vision lab at Linköping University, focused on developing AI-assisted techniques for picking out specimens for genome
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practice or other forms of appointment/assignment relevant to the subject area. The successful candidate must hold a PhD in one of the following fields: mathematics, physics, computational science, or
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Fluency in oral and written English It is meritorious that the applicant has Prior involvement in interdisciplinary projects combining computational and biological sciences. Familiarity with data management
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combining imaging techniques and data analysis to provide a more integrated picture of life processes in the context of health and disease. To be a postdoc fellow at the AMBER programme you will get
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Fluency in oral and written English It is meritorious that the applicant has Prior involvement in interdisciplinary projects combining computational and biological sciences. Familiarity with data management