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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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) program. Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular
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programming languages (e.g., Python, R). Experience working in a LINUX/UNIX environment. An excellent molecular biology skillset. Experience with NGS library preparation supported by a strong publication record
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efficiently interact in the interdisciplinary project. We seek candidates with a strong computer science, mathematics, statistics, or bioinformatics background and strong programming skills. Some previous
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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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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