344 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"UCL" Fellowship positions in United States
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(EHR), health information exchanges, and data analysis software. Experience with health IT innovation, including working with artificial intelligence, machine learning, telemedicine, or mobile health
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. Cross-Disciplinary Fellowships (CDF) are for applicants with a Ph.D. from outside the life sciences (e.g. in physics, chemistry, mathematics, engineering or computer sciences), who have not worked in
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immunology Experience with T cell engineering (CAR-T, TCR-T) and/or immunopeptidomics is preferred (but not required). At Dana-Farber Cancer Institute, we work every day to create an innovative, caring, and
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in each crop area and learn basic agronomic, data collection, and plant breeding methodologies in trials and nurseries planted at the USDA-ARS. Learning Objectives: The project assignments will provide
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of genes and proteins as regulators of physiological or immunological traits. Learning Objectives: Under the guidance of the mentor, the candidate will gain experience in and learn to utilize a functional
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related field. Desire to learn new skills and work in teams including students, researchers, and faculty. Excellent computer skills including Microsoft Word, Excel, PowerPoint, and statistical software
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help mentor undergraduate and graduate students and will have the opportunity to teach classes by separate assignment as a part-time lecturer. This position will begin Summer or Fall 2026 according
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the research and critical thinking is expected for this opportunity. Learning Objectives: The participant will engage in a comprehensive, hands-on learning experience designed to build expertise in laboratory
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invaluable hands-on experience and develop advanced skills while working closely with the Research Entomologist throughout all phases of the research process. This opportunity will allow you to learn and
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to learn. Interest in tumor metabolism and a strong desire to gain experience in bulk and spatial metabolomics. Solid bioinformatics skills, including familiarity with tools for analyzing omics datasets and