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. Data management skills and demonstrated experience managing, standardizing, synthesizing, and visualizing large, disparate natural resource (e.g., forest inventory, climate, land use, soils, elevation
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and their natural enemies. This research will leverage advanced 'omics' technologies and 'big data' analytics to unravel complex pest-natural enemy interactions, understand host associations, and
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management methods. The fellow will be a part of guided experimental design, data analysis, and manuscript preparation. Learning Objectives: To support the research and training of the postdoctoral research
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to cell and gene therapy. Will learn to use advanced manufacturing tools and strategies to gain a deeper understanding of challenges associated with T cell-based immunotherapies (such as CAR-T cells). Will
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-on experience that complements the participant’s educational and professional background and help the participant gain knowledge in processing and analyzing large volumes of bioacoustics data. Participants will
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generated quickly and regularly. Help develop machine learning techniques for feral swine abundance in data sparse environments. Collaborate with APHIS Wildlife Services (WS) to integrate data and model
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the participant’s educational and professional background and help the participant gain knowledge in processing and analyzing large volumes of bioacoustics data. Participants will use a range of spatial and
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biology, statistics, computer science, or a closely related field). Degree must have been received within the past four years. Preferred skills: Computer skills Knowledge and understanding of genome
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to multidisciplinary research aimed at advancing military medicine. What will I be doing? This opportunity offers a hands-on learning experience within a collaborative research environment focused on combat casualty
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near start of appointment. Preferred skills: Graduate training in genetics and biology or computer science Coursework in statistics and computer science Experience with computer scripting languages and