241 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"IFM" positions at Zintellect
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machine learning methods for disease quantification. Through the course of the project, they will gain in-depth knowledge of issues and the latest research at the junction of plant pathology and plant
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the discharges of wastes associated with conventional sorbent synthesis; • Learning on applied, cutting-edge projects with global impact while being mentored by the nation’s leading energy scientists
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for the Department of Defense, the U.S. Army and many other customers while also supporting ERDC’s research and development mission in geospatial research and engineering, military engineering, and civil works. ERDC
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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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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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. This fellowship is ideal for enthusiastic, team-oriented individuals eager to learn and make meaningful contributions to the field of emerging infectious diseases. Where will I be located? Frederick, Maryland What
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students and collaborate on aquatic ecology field projects in southeast Alaska wilderness watersheds. Learning Objectives: Learn about bioenergetic food web models to quantify food web energy fluxes between
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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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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