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Research Center for Molecular Medicine (CeMM), ÖAW | Graz 12 Bez Andritz, Steiermark | Austria | 3 months ago
; and how these mechanisms can be understood, modelled and ultimately perturbed for biomedical discovery. Two scientific tracks Track 1: Computational Biology / Machine Learning for membrane protein
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. Our dedicated and compassionate faculty and staff are driven by a common mission: Contribute to innovative approaches in predicting, preventing, and curing diseases, shaping the future of medicine
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of multiple surveillance and administrative data sources. Development of reproducible analytical workflows using programming languages such as R and Python. Application of machine learning and predictive
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from users and participating academies. They will be responsible for evaluating the performance of personalized training plan recommendation algorithms, predictive models of user evolution, and class
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, metabolism, protein interactions, mitochondrial function, translation and adaptive responses; and how these mechanisms can be understood, modelled and ultimately perturbed for biomedical discovery. Two
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. Our dedicated and compassionate faculty and staff are driven by a common mission: Contribute to innovative approaches in predicting, preventing, and curing diseases, shaping the future of medicine
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9th August 2026 Languages English English English We are looking for a Postdoctoral Fellow in statistical modeling for genomic data Apply for this job See advertisement This is NTNU NTNU is a broad
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energy imbalance (EEI) and ocean heat content (OHC), in order to close an existing knowledge gap and im-prove near-term predictions. Other partners in the project are University of Ber-gen and Nansen
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model for innovative medical education and a centre for transformative research. The School’s primary clinical partner is the National Healthcare Group, a leader in public healthcare recognised
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The postdoctoral fellow will work at the interface of epidemiology, causal inference, prediction modelling, responsible AI, digital health and global maternal and child health. The work will include development and