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) biological knowledge about GRNs from bioinformatics and system biology, (b) graph theory and topological data analysis for network modeling from mathematics, and (c) robust machine learning (ML) and GenAI from
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. The project explores the role of tumor-promoting inflammation in cancer progression through bioinformatics-driven, machine-learning and multi-omics analyses integrated with experimental data. Ideal candidates
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computational and statistical methods, with demonstrated experience in reproducible and scalable bioinformatics environments. The applicant will work in close collaboration with other Engblom lab team members who
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interpretable ML and/or generative AI, is required. Application to bioinformatics is a plus. About the employment The position involves full-time employment for a minimum of two years and a maximum of three years
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individual case. Additional requirements: Very good oral and written proficiency in English. Master’s level studies in a program with good preparation for research and appliction of bioinformatical approaches
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pipeline and implement it in a high-performance computing environment. Qualifications Requirements: A Master’s degree (or equivalent) in bioinformatics, biostatistics, computational biology, data science
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project where you will work at the Cytiva Solna and Elofsson lab environments, both located at the Solna Campus. Upon successfully completing the 4-year project, you will obtain a PhD in Bioinformatics from
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will contribute to field work, lab work and bioinformatic analyses including: Sample collection at Askö. Extraction of DNA, RNA, and protein. Analysis of meta-omic datasets. Integration of meta-omic and
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. The candidate will combine experimental and computational approaches. The project will start with bioinformatics-driven analysis, followed by integration of data generated from experimental models. Over time, the
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, computational modelling, bioinformatic analysis, and experimental vascular biology. Based in a dynamic translational research environment of data-driven life science, computational imaging, and vascular surgery