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biological systems and processes at all levels, from molecular structures and cellular processes to human health and global ecosystems. The SciLifeLab and Wallenberg National Program for Data-Driven Life
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, from molecular structures and cellular processes to human health and global ecosystems. The SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS ) aims to recruit and train the
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to build sequence dependent predictive deep learning models, and physical mechanistic models (thermodynamic and kinetic models etc.). Examples of suitable backgrounds: machine learning, programming
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model design and analysis as well as statistical model parametrization and validation techniques. This Postdoc position is part of a five-year research program funded by the Wallenberg Foundation, aimed
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Uppsala and in Sweden at large. For information about the SciLifeLab fellow program, see https://www.scilifelab.se/research/#fellows. SciLifeLab Fellows are also part of a broad national network of future
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analytical understanding; Proficiency in programming in Python and deep learning frameworks such as PyTorch and TensorFlow; Excellent communication skills in oral and written English; Creativity, thoroughness
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and global ecosystems. The SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS) aims to recruit and train the next generation of data-driven life scientists and to create
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position is part of a five-year research program funded by the Wallenberg Foundation, which aims to develop and apply computational tools to understand the evolution of biodiversity (see https
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at the Wallenberg Laboratory. The group is part of the national Data-Driven Life Science (DDLS) program, funded by the Knut and Alice Wallenberg Foundation. Their research focuses on developing computational methods
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degree in relevant fields (bioinformatics, immunology, computational biology, mathematics, and/or statistics). Strong programming skills in R and/or Python Demonstrated strong ability in analyzing high