14 machine-learning "https:" "https:" "https:" "https:" "https:" "Helmholtz Zentrum Geesthacht" research jobs at SciLifeLab in Sweden
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). The project focuses on developing computational models for cancer risk assessment, integrating multiple types of data and risk factors. The main objective is to design and apply machine learning and deep
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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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visiting: https://www.slu.se/en/about-slu/work-at-slu/ Location: Uppsala Form of employment: Temporary employment 24 months, with the possibility of extension. Scope: 100% Start date: 1st of September 2026
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on development of novel computational methods with state-of-the-art machine learning for gaining fundamental insights into healthy and diseased human tissues of the heart, cardiovascular system, and
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candidate, who is eager to learn and has a genuine scientific interest. Extensive knowledge in and practical experience with protein expression and structural characterization is mandatory. Documented
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of Medical Biosciences, which offers an international, collaborative, and open-minded research environment. Please visit the lab’s webpage for more information: https://erdemlab.github.io . The Erdem research
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aspects of both. The first direction concerns the data-driven discovery of dynamical rules underlying developmental trajectories. The aim is to develop and analyze quantitative frameworks that learn
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: October 2026 Full call details, eligibility criteria, application templates, and a matchmaking platform for identifying potential supervisors are available at: https://www.scilifelab.se/data-driven/ddls
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entitles you to several benefits through our collective agreement. Location: Solna More information https://bensonlab.se/ Application An employment application must contain the following documents in English
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. Our research is focused on cell biology, spatial proteiomics and machine learning for bioimage analysis. The aim is to understand how human proteins are distributed in time and space, how this affects