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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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development of phylogenetic methods. The EvonetsLab is supported by a Starting Grant from the European Research Council and a DDLS Fellowship from the SciLifeLab and Wallenberg Swedish program for data-driven
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on documented qualifications regarding programming, machine learning, AI tools for image analysis. Knowledge of Python, Matlab, C/C++ or similar programming language is an advantage. Consolidated experience with
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computational drug metabolism project in collaboration with AstraZeneca and Chalmers University of Technology, funded through the Wallenberg National Program for Data-Driven Life Science (DDLS). Chalmers
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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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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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evolutionary biology, and proficiency in using necessary software will be considered. Experience in a compiled programming language like Fortran, as well as with high-level languages – for example, R
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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
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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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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