64 software-formal-method-phd Postdoctoral positions at University of Minnesota in United States
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development; and opportunities for outreach and community engagement. Qualifications Required Qualifications: PhD in limnology/oceanography/microbial ecology or related field Preferred Qualifications
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, Indigenous, and people of color, those with disabilities, those who are first generation, veterans, and those from 2SLGBTQIA+ communities. The postdoc will be formally mentored by Dr. Xiao Zang and will engage
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. Publish research findings in peer reviewed journals. Pursue your own research interests within the broader theme of the position. Data Acquisition Methods and Practice (40%) Support staff involved in infant
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on application materials. Required Qualifications: • PhD in Immunology, Molecular Biology, or a closely related biomedical field • Strong foundation in cellular and molecular immunology, with demonstrated
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on application materials. Required Qualifications: • PhD in Immunology, Cell Biology, or related biomedical sciences • In-depth scientific expertise in cell death, macrophage biology, and fibrotic disease
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, fellows and other inexperienced professional persons in proper laboratory methods and procedures. Qualifications Required Qualifications: • A Doctorate Degree (PhD, which is completed within the last 3
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. If the applicant has not completed their degree, they will be hired as a predoctoral associate (9545) until their PhD is conferred. Percentage breakdown of duties: 20% Captures and collars coyotes and foxes in urban
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mentor undergraduates, graduate students, and/or researchers in the lab. Qualifications Required Qualifications: PhD in biochemistry or a related field. At least one first author publication, including
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include: -PhD (or equivalent terminal degree) in relevant discipline, in biological sciences, microbiology, chemical engineering, biomedical engineering, or mechanical engineering -Experience with funded
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methods of data analytics (e.g., statistics, stochastic analysis, Bayesian statistical analysis), physically-based hydrology and water quality models, and the use of machine learning tools for modeling flow