43 algorithm-development-"University-of-Surrey" Postdoctoral research jobs at Duke University
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resistance/relapse following immunotherapy such as CAR T and developing novel agents for protecting hematopoietic stem cells following radiation exposure. The overall duties and responsibilities are: 1
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structure-based ligand design. We are dedicated to advancing scientific knowledge and developing novel solutions in chemical synthesis, chemical probe development, and drug discovery. We invite highly
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translational studies of patient samples, such as scRNAseq, metabolomics and proteomics, to develop an accurate model of JDM. The model will serve to better understand disease triggers, identify more helpful
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3D stem cell culture, human peripheral blood mononuclear cell (PBMC) isolation, endometrium/trophoblast model · co-culture, likely in the presence of immune or vascular cells · Prepare cell culture
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. Occupational Summary The David Lab at Duke University (www.ladlab.org ) is recruiting a postdoctoral fellow to join an established research group developing and applying DNA sequencing and computational
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new NIH-funded Center for Excellence in Multiscale Immune Systems Modeling. This position focuses on leveraging and developing new equation learning methods, such as Physics-Informed Neural Networks
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, neurobiological, and clinical data to develop and validate predictive models of psychiatric risk. Prepare manuscripts for peer-reviewed journals and present findings at national and international conferences
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: Engineering / Biomedical Appl Deadline: none (posted 2025/06/16) Position Description: Apply Position Description Chory Lab Seeking Postdoctoral Associate (Automated Evolution postdoc) This postdoctoral
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, and behavioral measures. · Collect, process, and analyze multimodal datasets, including neural, physiological, and motion-tracking signals. · Develop and refine research protocols and methodologies in
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Systems Modeling. This position focuses on leveraging and developing new equation learning methods, such as Physics-Informed Neural Networks (PINNs), Biologically Informed Neural Networks (BINNs), and