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· Part time one year contract available · Contribute to a breast cancer research program · Base Salary starting from $116,916 + 17% superannuation ( Pro rata) About the opportunity
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field. * Minimum three years of research experience in computational modeling of brain circuits. * Demonstrated expertise in the Neuroblox computational neuroscience platform, including direct knowledge
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computational scientists and experimental biologists, contributing to the advancement of predictive models for cancer initiation, as well as helping identify potential biomarkers for early detection and treatment
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temporal reasoning ultrasound AI tools. Thus, the work will involve both computational methods research and collaborating with clinical domain experts to design and evaluate models in simulated and real
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 5 hours ago
Postdoctoral Program website for application instructions and requirements: How to Apply | NASA Postdoctoral Program (orau.org) A complete application to the NASA Postdoctoral Program includes: Research proposal
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this project, you will combine experimental paradigms, fMRI, and computational modelling to uncover mechanisms underlying risk and resilience. You will work with a rich multimodal dataset and collaborate within
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, Job/Project description: The AgroBioSciences Program (AgBS) at the Mohammed VI Polytechnic University is seeking a post-doctoral fellow in Modeling and Crop Yield Prediction in Africa. The candidate
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description context: The rapid expansion of Artificial Intelligence has generated a
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decision is made. Demonstrated experience with constraint-based genome-scale modeling, resource allocation modeling, or other computational models of metabolism, including hands-on use of established tools
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well as interpretability of scientific foundation models. The rush to build foundation models has led to the development of large machine learning models in Astrophysics, fluid dynamics, biology, weather prediction, solar