46 programming-"INSAIT---The-Institute-for-Computer-Science" positions at SciLifeLab in Sweden
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Starting Grant from the European Research Council and a DDLS Fellowship from the SciLifeLab and Wallenberg Swedish program for data-driven life science. The successful candidate will be working within
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and experiences. We regard gender equality and diversity as a strength and an asset. The SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS) is a 12-yr initiative funded with
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, especially Bioinformatics, program the applicant must have passed courses within the first and second cycles of at least 90 credits in either, a) Chemistry/Molecular Biology/Biotechnology, or b
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Program for Data-Driven Life Science (DDLS ) and the student joins its research program . Supervision: Associate Professor Hossein Azizpour What we offer Admission requirements To be admitted
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) environments. Strong programming skills (e.g. TensorFlow, PyTorch, scikit-learn). AI/ML applications in life science. Large-scale data management (databases, data curation, metadata management, FAIR, etc
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KTH Royal Institute of Technology, School of Engineering Sciences in Chemistry, Biotechnology and Health Project description Third-cycle subject: Medical Technology (Joint KTH-KI program) In
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previous experience of the Spatial Transcriptomics method and data analysis as well as knowledge of the programming language R. The PhD student will be at KTH, Department of Gene Technology, SciLifeLab
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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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. 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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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