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new therapeutics and will be in charge for neuromodulation and neuroimaging hardware and software arrangements, collecting and analysis of data, and publishing the new discoveries. Note: Position tasks
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at the University of Minnesota seek a motivated scientist with applied field research experience to evaluate existing data from research trials conducted in Minnesota and establish and coordinate nitrogen fertilizer
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analyze data for experiments evaluating vernalization requirements in different turfgrass species such as perennial ryegrass and hard fescue. Investigate the molecular regulation of vegetative-reproductive
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%). • Contribute to data and lab management (5%) Qualifications Required Qualifications: • PhD, DO, MD or similar degree in health sciences or related field • 3+ years experience in biological sciences laboratory
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and Benefits Pay Range: $62,232 annually; depending on education/qualifications/experience Please visit the Benefits for Postdoctoral Candidates website for more information regarding benefit
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Preferred Qualifications: • Demonstrated productivity through first-author and collaborative publications in immunology • Strong background in experimental design, statistical data analysis, and data
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applications from diverse candidates and are committed to creating an inclusive and supportive research environment. Job Responsibilities Data Analysis and Publication (50%) Test hypothesis around developmental
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to Apply Interested candidates should submit the following documents via email: · A current CV or resume. · A cover letter describing research experience, interests, and career goals. · Contact information
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extraction and RT-PCR. Prepare samples for next generation sequencing (NGS) and analysis of NGS data. Assist in projects involving bacteria and bacteriophages. Work after hours and on weekends as needed. Use
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implementation of various projects, including (but not limited to) scaling, algorithm development, scaled score development and documentation. Support the creation, management, and retention of large-scale data