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Computational Postdoctoral Fellow (Quantitative Modeling Group) - 106785 Division: BE-Biological Systems & Engineering Berkeley Lab’s (LBNL, https://www.lbl.gov/) Biological Systems and Engineering
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objective prediction of biological aging, but also the improvement of age-related phenotypes such as cognitive decline, muscle weakness, bone density loss, and kidney dysfunction. Our research is particularly
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predictive modeling and validation techniques. Research & Publication: Skilled at critically reviewing literature, designing rigorous studies, and producing publications for high-impact journals. Collaboration
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Research Center for Molecular Medicine (CeMM), ÖAW | Graz 12 Bez Andritz, Steiermark | Austria | 2 months ago
intelligence and machine learning to decode interaction archetypes of membrane proteins and predict the effect of genetic variants. While the Superti-Furga Lab will be based in Graz, regular travel to Vienna
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of Defense (DoD) is offering a post-doctoral fellowship at the U.S. Army Medical Research and Development Command - Institute of Surgical Research (USAMRDC ISR) within the Expeditionary Medical Systems (EMS
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collaboration with the group of Peter Sykacek at BOKU, Vienna. The project uses artificial intelligence and machine learning to decode interaction archetypes of membrane proteins and predict the effect of genetic
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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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predictive modeling and validation techniques. Research & Publication: Skilled at critically reviewing literature, designing rigorous studies, and producing publications for high-impact journals. Collaboration
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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
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that integrate prediction and control algorithms, optimizing data transformations, offloading and distributed computing, and exploiting mechanisms such as network slicing and multi-access edge computing