32 genetic-algorithm-computer "Integreat Norwegian Centre for Knowledge driven Machine Learning" positions at SciLifeLab
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information about us, please visit: www.dbb.su.se Project description We are seeking a researcher for a fixed-term project within the framework of a research program on allosteric modulation. The project
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genetic, phenotypic, and environmental data, testing when and how evolution can be forecast. As a PhD student in our group, you will gain hands-on experience in computational and mathematical modeling and
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DNA unit, you are part of a team that includes staff at Stockholm University, and is part of a research environment that includes the Human Evolution research program at Uppsala University and the
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(iPanCare ) Lab. We are a part of the SciLifeLab & Wallenberg National Program for Data-Driven Life Science (DDLS ). iPanCare lab conducts research in the field of precision diagnostics and medicine
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project to study genetic regulatory variation and its link to molecular, cellular and organismal phenotypes using a systems genetics approach. The project is fully computational, and potential approaches
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medicine, focusing on the onset of disease and how we can improve diagnostics and treatment for patients. Some of our strongest areas with world-class research deal with cancer, genetics and blood. We kindly
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”. Qualification requirements Required Academic degree in Bioinformatics, Computer Science, Biotechnology or similar. Programming experience, preferably using Python or Javascript. Basic knowledge of version control
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, computer science or a related subject the employer considers of relevance to the position. Experience (3+ years) in working with advanced bioinformatics analyses of omics data from high throughput
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administrative support systems Solid computer skills and proficiency in Microsoft Office (including Excel), and the ability to adopt new digital tools is required. Fluency to express yourself in speech and writing
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and accepted to the PhD program at Stockholm University. Project description Project title: “Deep learning modeling of spatial biology data for expression profile-based drug repurposing”. A new exciting