131 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" Fellowship positions at Zintellect
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: Research activities will be conducted in BSL-2+ laboratories. Learning Objectives: Under the guidance of a mentor, the participant will gain experience in: Animal studies: mouse and large animal inoculation
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information needed to inform management of the disease. Specific areas of investigation will be based upon the participant’s expertise and interest. Learning Objectives: Under the guidance of a mentor, the
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to join this development team as a fellow and learn to create, evaluate, and validate rapid, accurate, and sensitive diagnostic methods for detecting disease pathogens. The fellow will have an opportunity
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projects related to comparative effectiveness and patient-centered outcomes research, all in support of Office of the Secretary priorities led by ASPE. Learning Objectives: Under the guidance of a mentor
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of incorporating sensors, spectroscopy, imaging, and machine learning techniques into the postharvest processing workflows and/or pre-harvest evaluation of food quality and safety. The participant will have the
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, focusing on gene editing and molecular breeding techniques. While flowering in sugarcane is an undesirable trait for Florida farmers, it plays a crucial role in crossing and breeding. Through this learning
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an enhanced user interface that incorporates various functionalities to support adverse event analysis. Learning Objectives: You will join generations of scientists in the field of pharmacoepidemiology
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. Learning Objectives: You will join generations of scientists in the field of pharmacoepidemiology, pharmacovigilance, and drug safety through this learning opportunity. You will receive mentorship by experts
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. Learning Objectives: The selected fellow in this project will have the opportunity to contribute and advance their knowledge and skills in wood products carbon related research that will involve maintaining
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evaluate how these different extraction processes impact the nutritional profile, physical properties, and effects on appearance, palatability, and flavor of a food product (functionality). Learning