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on high-performance computing (HPC) systems. Closely Collaborate with Clinicians and Wet-Lab Scientists on the experimental design and collect data for computational modelling and analysis. Engage Actively
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evaluating them on real-world data (e.g., in iCAN ) in collaboration with precision cancer medicine experts. We strive to revolutionize cancer care through the power of massive data and machine learning! Key
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complement the scientific profile of the Molecular and Integrative Biosciences Research Programme: https://www.helsinki.fi/en/faculty-biological-and-environmental-sciences/research/molecular-and-integrative
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-Cell Genomics through the NORPOD program NORPOD is a collaborative postdoctoral program of the Nordic EMBL Partnership for Molecular Medicine . The partnership is a network of four national research
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using unique novel mouse models, spatial technologies and analytical methods. Postdoctoral Researcher in Functional Cancer Microbiome through the NORPOD program NORPOD is a collaborative postdoctoral
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biogeochemistry, environmental sciences, or a related field. A successful candidate should be able to: Design, conduct, and report research within the scope of the project Contribute to teaching within
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Assistant Professor/Associate Professor or Professor in Ecological Restoration of Urban Environments
for the position, attention will be given to scientific publications and their significance in the applicant’s field of research, teaching experience and skills and pedagogical competence, ability to produce
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forest sciences degree programs and in the university-level Liberal Arts and Sciences (LAS) program. The Department of Forest Sciences offers the LAS program "Resource management of global forests" study
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will design and apply a range of in vitro techniques, including quantitative RT-PCR, recombinant protein production, and bacterial and mammalian cell culture assays; as well as in silico techniques
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the candidate can start in autumn 2025. Background Our group develops and applies systems pharmacology strategies to design rational combinatorial therapies for cancer. We combine both computational (dry-lab) and