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that universities, companies, and venture capital firms don't fund because they view it as too risky. We prefer to use the word Create a Job Match for Similar Jobs About Harvard University Harvard University is
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data-driven modelling methods for renewable energy integration. Research Outputs and Funding: Publish high-quality research outcomes, contribute to milestone reports, collaborate on competitive research
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monitoring applications. Under limited supervision, the Postdoctoral Fellow will collaborate with the PIs to design and conduct field- and modeling-based research. In this position the Fellow will: Develop
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and functionally validate antibodies targeting tau in neurodegeneration in vitro and in mouse models, undertake data analysis, prepare manuscripts, publish high-quality research and present findings
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project. · Architect and evaluate multi-site cardiotoxicity risk prediction models integrating structured EHRs, clinical notes via natural language processing, strain echocardiography features, and
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, delay thermal breakthrough, and enhance long-term thermal recovery from EGS. This position also aims to model, evaluate, and optimize innovative engineering solutions, including chemical, mechanical
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focused on the development and application of recycled and waste-derived materials for advanced engineering systems. The role will emphasise computational modelling, simulation, and data-driven approaches
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Oden Institute for Computational Engineering and Sciences | Austin, Texas | United States | 3 months ago
genetic data Multimodal machine learning for biological discovery Translational genomics and risk modeling The fellow will work in an environment that emphasizes methodological innovation, statistical rigor
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Medical Computer Vision Experience with Large Language Models and Generative AI Experience working with real-world EHR and imaging data Experience working with PACS and the DICOM standard Preferred
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Berkeley Lab’s (LBNL ) Biological Systems and Engineering (BSE ) Division has an opening for a Computational Postdoctoral Fellow to join the Quantitative Modeling Group led byHéctor García Martín