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Field
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projects that apply machine learning and advanced computational modeling to integrate multi-omics, clinical, and imaging data for biomarker discovery and mechanistic insights in AD. The position offers
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About the Position We are recruiting a Postdoctoral Research Associate to join Tom Hartvigsen’s research group in UVA’s School of Data Science. The postdoc will work on developing machine learning
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fellow, you will be empowered to own a project end-to-end, from model design and assay development to data generation, analysis, and publication. You will be immersed in a scientifically rich and
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 17 days ago
to contribute to innovative projects at the forefront of healthcare delivery improvement, leveraging Large Language Models (LLMs) and clinical data analysis. About the Position Our Postdoctoral Research Program
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outputs are biologically and clinically meaningful. Contribute to PI-led grant applications and mentor undergraduate/graduate students. Qualifications: Required: PhD in Computer Science, AI, Data Science
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: 278915095 Position: Postdoctoral Associate: Integrating political economy insights into energy modeling Description: The Peng group in the School of Public and International Affairs and the Andlinger Center
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specified by the Principal Investigator. Postdoctoral position in computational modeling of anxious avoidance at the Computational Mechanisms of Psychopathology Lab at Emory University (PI: Vanessa Brown, PhD
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are sought. Applicants will have an engineering PhD, or equivalent degree and experience in a relevant field. Ideal applicants will have experience in energy-system transition modeling, linear and mixed
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is required. Experience with experimental design, data analysis, and/or modeling. PREFERRED QUALIFICATIONS Previous experience, education, or general proven knowledge in hearing or speech and language
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models Disseminate research through publications, presentations, and open-source contribution Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in Materials Science, Data