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and understanding of data-dependent and data-independent acquisitions (DDA, DIA). Preferably, experience with FAIR workflows including use of open science software and chemical informatic resources
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science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes to human health and
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The Department of Gene Technology, at KTH Royal Institute of Technology, is looking to fill a position as Assistant Professor focused on innovative development and application of computational
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the national Data-Driven Life Science (DDLS) program. About the position and the project As an industrial PhD student, you will be employed by the startup company PredictMe AB while being formally enrolled as a
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requirements, the applicant must have credits in Life Science, Computer Science Mathematics, Physics or Bioinformatics or alike, including a 30 credit Degree Project (thesis). proficiency in English equivalent
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need to fulfil the following requirements: PhD in one of the following fields: bioinformatics, molecular biology, computer science or related subjects the employer considers of relevance to the position
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. Requirements University degree in bioinformatics, computer science, IT, or a related field. At least three years of documented work experience in bioinformatics-related systems development. Excellent knowledge
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into consideration. We are looking for someone with a doctoral degree in computational physics, applied mathematics, computer science, bioinformatics, structural biology, or a related field. Documented experience in
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studies. About the DDLS program Data-driven life science (DDLS) combines data, computational methods, and artificial intelligence to study biological systems from molecular structures to human health and
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-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 processes to human