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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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modeling, machine learning, and AI techniques applied to biomedical data is a plus. Clinical Proteomics: Experience with clinical trial data, real-world evidence (RWE), and biomarker-driven trial designs is
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: The primary location will be at the KI Flemingsberg campus, but since the project is a collaboration with the SciLifeLab DDD platform some parts of the project will also be performed in Solna. https
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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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-performance computing. SLU provides access to extensive datasets that can be used to develop machine learning methods and automated analyses relevant to the position. Long-term datasets are available from, i.a
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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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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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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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at Sahlgrenska Academy of relevance include genomics, metagenomics, culturomics, proteomics, transcriptomics, software development, machine learning, and other statistical analyses of large-scale health data
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at https://nbis.se. Duties We are seeking a candidate who wants to help enable life science research in Sweden that goes beyond what is achievable by individual researchers, a single university, or a single