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Lab (https://pwrlab.org/ ) at the University of California San Diego is seeking a highly motivated Postdoctoral Research Scholar to contribute to a two-year project focused on helping Southeast and
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of how mechanical and chemical forces change biofouling or anticoagulation behavior through the development and testing of new multilayered soft robotics platforms. This project will involve collaborative
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the United States and globally. These research efforts involve participating in the development, evaluation, and implementation of task-shared mental health services in primary care settings and other community
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testing in molecular evolution. The individual will use methods such as RNA-seq to identify genes and regulatory sequences that drive plant toxin detoxification, transport, and resistance, and potentially
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Summary Carry out a research project in Dr. Peterson's lab. Career Readiness Competencies: Career & Self-Development Communication Critical Thinking Teamwork Essential Functions Conduct chemical
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 1 hour ago
to): Develop machine learning algorithms that utilize fire products from geostationary satellites to better represent fire evolution and variability Develop machine learning emulators to represent forward
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be provided with generous funding of $2,000 towards their professional development during the course of the year. The resident/s will have discretionary use of these funds (e.g., they can be used
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understanding of how mechanical and chemical forces change biofouling or anticoagulation behavior through the development and testing of new multilayered soft robotics platforms. This project will involve
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. - Contribute to the development of risk-prediction tools, biomarker panels, and precision-medicine algorithms. - Participate in NIH-funded translational studies involving spatial multi-omics, proteomics
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at https://academicpositions.harvard.edu/postings/15947 . Contact: Pragya Sur Email: Postal Mail: 33 Oxford St. Suite 113 Cambridge, MA 02138 Web Page: https://statistics.fas.harvard.edu/