282 evolution-"https:"-"https:"-"https:"-"https:"-"https:" Fellowship positions in United States
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Project: Selected participants will join research projects focused on the development of methods and tools in support of our regulatory science efforts in evaluating computational pathology (CPATH) devices
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development. Conduct evolutionary genomics analyses, including population structure, local adaptation, and genome-wide scans. Develop and implement GWAS and QTL mapping pipelines for trait discovery. Perform
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movement behaviors to health outcomes, and/or the development and optimization of mHealth interventions. Propose and write manuscripts based on the conducted research. Work with mentors in developing
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Program Faculty Director to align the program’s academic components with the university’s academic standards and criteria. Partner with the University Development Office and the Provost’s Office to explore
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sciences. The research interests of the candidate can be one or more of the following topics. Projects that address change across time or across nations in different stages of development are encouraged
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the development and evaluation of cropping systems that include alfalfa and other perennial crops that are designed to improve soil health, increase productivity and efficiency, and build resilience. This project
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Fellowship program offers comprehensive research, training and professional development opportunities for scholars advancing their careers in history. Fellows pursue their research with support from
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fellow to join our studies on the genetic basis of human evolution, with a focus on the evolution of the human brain. Candidates with a strong track record in any biological field are welcome to apply
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stakeholders and assisting with the development of a new IHP-Dearborn project site. Required Qualifications* Ph.D. in History, with deep subject knowledge of AAPI cultural history. Must have a Ph.D. in hand by
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. This position will be involved in a combined applied and methodological genetics project. This project will focus on the development and implementation of ancestry (admixture) based detection and characterization