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machine learning, causal inference, or mediation analysis applied to critical care outcomes. Knowledge of ECMO physiology, device characteristics, and related outcomes research. Demonstrated success in
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knowledge within the realm of political science. They should be proficient in conducting quantitative analyses. Experience with large language models, machine learning, and/or programming in R or equivalent
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timely and professional manner. Engaging in professional development training and learning any area of immigration law they are not already familiar with. Continuing to upgrade knowledge, skills, and
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position under the supervision of Dr. Chris Smith Home | Chris Smith . Our new lab in Evolution, Ecology, and Behavior investigates machine learning approaches for population genetics. Our research
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partnerships with the U.S. Military and U.S. Department of Veteran Affairs, through UCLA Operation Mend. In our two-year clinical and research fellowship, trainees will work closely with clinic attending
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spatial and temporal data analysis using advanced machine learning technologies. The successful candidate will become a part of an interdisciplinary team working to develop machine learning techniques
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antigens, T cell receptor (TCR) and antigen interactions and their crucial role in anti-cancer immune responses. You'll leverage your strong background in computational biology, machine learning, and
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Lawrence Berkeley National Laboratory - Physics | Berkeley, California | United States | 27 days ago
), quantum information science (sensing and simulations), and artificial intelligence/machine learning. Research areas highlighted for 2026 include ATLAS, rare event searches with quantum sensors, DUNE
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and/or digital culture). In addition to conducting their own research, supported by faculty mentorship, the Fellow will be expected to teach two courses per year: one lower-level course, such as
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areas such as data analysis, statistical modeling, machine learning, numerical modeling, or remote sensing Preferred Qualifications A general understanding of ecosystem modeling or ocean circulation