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scientific independence Applicants are not expected to have experience in all of the areas listed above. Candidates with complementary expertise and an interest in learning new approaches are encouraged
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include: Understand the extent of existing digital images of text, and how the information locked away in them would advance provenance understanding Acquire additional external data, such as the Getty
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Research Initiative on the History of Sexualities and is expected to participate in their activities and to teach one course during the fellowship. Compensation is commensurate with education and experience
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collaborative work, as evidenced by publications or preprints. Enthusiasm for learning neuroimmune biology is essential; prior formal immunology training is not required. Mentoring, training, and collaborations
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skills, including generalized linear models, multiple machine‑learning algorithms, MOFA and multi‑omics pathway analysis. · Strong background in experimental design, quantitative data analysis, and
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) independence to lead a project as well as willingness to work in a team; (g) an open mind to learn new methods from junior researchers and collaborators; (h) good scientific presentation and writing skills
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include: Biomedical sensing and physiological monitoring Edge intelligence and energy-efficient machine learning hardware Radar and wireless signal processing and communications The successful candidate
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, the Peabody Museum, or more technical parts of the University for periods of time to learn about both research and operational workflows. Connections with the Wu Tsai Institute, the AI at Yale program, the Data
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Postdoctoral Associate | Mitochondrial Genomics | Lake Lab — Yale University, Department of Genetics
track record of impactful research outcomes Manuscripts published in peer-reviewed journals Ability to work both independently and as part of a team Eagerness to learn and establish new methods, and good
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epidemiologic and statistical methods, including causal inference approaches, machine learning techniques, and high-dimensional data integration methods. Prepare first-authored manuscripts, abstracts, progress