10 phd-data-mining Postdoctoral research jobs at Missouri University of Science and Technology in United-States
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production. In carrying out their duties, the successful candidate will conduct literature searches relevant to assigned research projects, safely handle radioactive materials, obtain and analyze data from a
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Missouri University of Science and Technology | Rolla, Missouri | United States | about 2 months ago
for publication; and assisting in the training of graduate students and new lab members. Work Hours: 8 a.m. to 5 pm., occasional evenings and weekends Qualifications Minimum qualifications • PhD in biomedical
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PhD in immunology, cell biology or a related field by start of appointment. Candidates will be evaluated on: Proficiency in cellular biology and multicolor flow cytometry and previous experience with
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veterinary pathobiology. Qualifications PhD in any field of biological sciences (candidates with a DVM, PhD are encouraged to apply but not required). Candidates will be evaluated on: Strong background in
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-on, operational knowledge of both GC-MS and UHPLC-MS/MS instrumental analyses and data processing. The successful candidate will focus on data generation and metabolomics analyses of various American Elderberry
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gland fibrosis. The candidate will develop and execute using cell culture and vertebrate animal testing, data analysis, manuscript preparation, presentation of results, and working with collaborators and
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longitudinal data sets including samples of mothers, fathers, and infants that continue to be analyzed and published. Dr. Groh's lab also regularly conducts meta-analyses to evaluate developmental questions in
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of Veterinary Medicine; and MU Institute for Data Science and Informatics at University of Missouri (MU). The Wan Lab currently holds more than $28 million in committed grant funding. The lab is physically
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. Congress and stakeholders with data and policy analyses focused on regional agricultural financial outcomes. Through a coordinated multistate effort, RaFF evaluates how policy decisions and innovations
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will be evaluated on: • Prior knowledge and demonstrated expertise in next-generation sequencing data analysis, computational systems biology, and/or data integration; • The ability