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these bioinformatic experiments. Access to a high-performance computer will be provided. The candidate must be capable of generating complex molecular compound models in silico and using current molecular dynamic
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National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | about 1 hour ago
modelling of trace gas emissions are also considered a strength. We encourage research proposals to explore questions around the use of plume imaging technology to geolocate and quantify natural emissions
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function. Knowledge and/or experience in high dimensional and conventional flow cytometry. Mouse handling and tissue processing. Generation and analysis of bulk and/or single cell transcriptomic data
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Status: Exempt Work Schedule: Monday – Friday, 8 a.m. – 5 p.m. Summary Our brain tumor research laboratory is currently seeking outstanding young scientists to join our group as Postdoctoral Research
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experience in: Deep learning Medical imaging computing (preferably neuroimaging) Computationally efficient deep learning Deep learning model generalisation techniques. Translating deep learning models
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logging and analysis and manipulating well-log data and integrating rock observations to develop basin-scale models. Relevant peer-reviewed publications and conferences papers on Lata Paleozoic Ice Age
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(preferably neuroimaging) Computationally efficient deep learning Deep learning model generalisation techniques. Translating deep learning models to the clinic The post holder will be based in the Department
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Physical Biology Lab and/or to pursue individual projects in each lab. The Project Environmental issues are currently among the most pressing facing humankind. As such, understanding how students learn about
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of Veterinary Medicine; and MU Institute for Data Science and Informatics at University of Missouri (MU). The Wan Lab currently holds more than $28 million in committed grant funding. The lab is physically
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combining these tools with theoretical models, we aim to understand how the brain supports thoughts, emotions, and decisions—and how disruptions or biases in these processes impact mental health. CAHBIR