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Job related to staff position within a Research Infrastructure? No Offer Description As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff
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reviewed annually at a minimum and are subject to change at any time, and for any reason, throughout the course of employment. Learn more about the work modes . U-M EEO Statement The University of Michigan
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, economic evaluation, and surveillance to learn how to operationalize, and when needed, improve analytical tools. Research activities will support rapid risk assessment, emergency preparedness, and
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. Research Project: Joining a team of landscape and fire ecologists to learn about and support geospatial analysis of fire mitigation implementation in the highly fire prone lands of Kona and Kohala on Hawaii
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to staff position within a Research Infrastructure? No Offer Description As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the
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1-year fellowship in Shoebill Conservation Genetics with support for a further 3-year PhD fellowship
biology, or conservation completed before 31 July 2026. In addition to an interest in evolutionary and conservation biology, the candidate should be committed to doing field work, wet-lab work, learning
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provides financial support and resources to medical students to spend a summer focusing on anesthesiology research, training in scientific methodology and techniques, and learning how to incorporate research
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time-management skills are a must. Research grant writing experience and a publication track record are highly desired. Preferred Qualifications: Expertise in machine learning, deep learning, natural
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the relative importance of processes in simulating the CMRB agroecosystem. Learning Objectives: Under the guidance of the mentor, the participant will: Learn how cropping system design must align with local soil
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computational pipelines for multiplex imaging, spatial transcriptomics, single cell RNAseq, and multi-omics data integration. Lead graph-based network and machine learning analyses of tumor immune