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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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, incorporating their own ideas and experience in computer vision, machine learning, and related fields, to further visualization and interpretation of molecular images. Our research environment focuses
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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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, international, and outward-looking work environment located in the lively city of Gothenburg on the west-coast of Sweden. The position is funded by the fellowship scheme of the Wallenberg National Program for
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(Stockholm, Sweden) and the candidate will benefit from a strong (inter-)national network of collaborators in protease biology and computational proteomics. The successful candidate for this position will join
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internationally outstanding research in the life sciences. Project description We seek two highly motivated postdoctoral researchers to develop new mathematical and computational methods for modeling developmental
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life science technologies with data and AI expertise. Computational methods and artificial intelligence applied to large-scale molecular data are transforming the study of biological systems at all
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data on our dedicated high-security compute cluster Miarka at UPPMAX, as well as on local servers. Automation of data handling and integrating systems for laboratory tracking (samples, steps, reagents
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methods. Good computer skills. Meriting Qualifications Documented theoretical or practical experience in structural biology and/or mass spectrometry. Experience in project management and communication with
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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 processes