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for the prediction of enzymatic activities and reactions from amino acid sequences; (ii) validation and extension of models and tools for the prediction of activities and properties of natural compounds; (iii
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decision-support tool that quantifies the accuracy of mechanistic electrophysiology model predictions for drug-induced changes to electrophysiology observed in animal cardiovascular safety studies. We
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well as AI-driven approaches for treatment outcome prediction and clinical decision-making. Projects involve multimodality imaging data, including CT, MRI, PET, and Ultrasound, as well as clinical radiation
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, to becoming more involved in the bioinformatic and analytic aspects of predictive modeling. As such, the Postdoctoral Computational Biologist should have a willingness to learn new languages and tools as the
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Posting Number R260058 Posting Link https://www.ubjobs.buffalo.edu/postings/61964 Employer Research Foundation Position Type RF Professional Job Type Full-Time Appointment Term Salary Grade E.89 Posting
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Research Center for Molecular Medicine (CeMM), ÖAW | Graz 12 Bez Andritz, Steiermark | Austria | 2 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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, molecular biology, cell biology, immunology, and in vivo model systems. For more information about Dr. Zhaohui Gu’s lab, please visit: https://gu-lab.net and https://www.cityofhope.org/Zhaohui-Gu As a
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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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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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page to watch video, or click here to open video) About the position The position is part of the research project “Prediction of genetic values and adaptive potential in the wild (GPWILD)” (https