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expression, cell state-specific regulatory programs, and clinical outcomes. Related projects will include: Develop and apply statistical or machine learning approaches to model the effects of common and rare
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research in cardiovascular and autonomic (i.e., bowel, bladder, sexual and cardiovascular) dysfunctions following SCI Demonstrated expertise in current machine learning techniques applied to biological
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Center for Biologics Evaluation and Research (CBER) | Silver Spring, Maryland | United States | 8 days ago
such as CAR-T cells and develop novel strategies to improve safety and efficacy of T cell therapies. Learning Objectives: The overall learning experiences you will gain are as follows: Will learn to perform
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Geosciences division is hiring an Autonomous Material Processing Postdoctoral Fellow to help transform how critical materials are produced. In this role, you'll bring together machine learning, real-time
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that are tailor-made to the research questions and data of CREATE. The successful candidate will conduct advanced methodological and psychometric research. Potential topics include (a) AI, machine learning, and
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to cell and gene therapy. Will learn to use advanced manufacturing tools and strategies to gain a deeper understanding of challenges associated with T cell-based immunotherapies (such as CAR-T cells). Will
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Date: August 15, 2026 (negotiable) Specialty Areas: Computational Linguistics, Language Acquisition, Cognitive Modeling, Machine Learning The Department of Linguistics at the University of Michigan
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total. No one can be appointed for more than one Postdoctoral Research Fellowship at the University of Oslo. Postdoctoral fellows who are appointed for a period of four years are expected to acquire basic
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computational chemistry, reaction network analysis, and machine learning for organometallic catalytic reactions. 2. Design of membrane-permeable macrocyclic peptide drugs via machine learning structure
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research position under the supervision of Dr. Chris Smith Home | Chris Smith . The lab— in the Evolution, Ecology, and Behavior section—investigates machine learning approaches for spatial population