10 assistant-professor-computer-"https:"-"https:"-"https:"-"https:"-"UCL" Postdoctoral positions at The University of Arizona
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Associate I, Information Science Posting Number req25315 Department Information Science Department Website Link https://infosci.arizona.edu/ Location Tucson Campus Address Tucson, AZ USA Position Highlights
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-security sensitive) Number of Vacancies 1 Target Hire Date 5/1/2026 Expected End Date 5/1/2027 Contact Information for Candidates Alonso Favela, Ph.D. Assistant Professor, Plant Science alonsof@arizona.edu
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cleaning, including study data codebooks and data management and sharing plans. Help oversee a team of research assistants to conduct the studies, including all stages of the process from recruiting
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Postdoctoral Research Associate I, Psychology (Genetically Informed Studies of Social Connectedness)
applicant with demonstrated experience with advanced statistical methods, including a focus on causal inference, bioinformatics and computation (more broadly), or other cutting-edge analytic tools
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experiments with graduate students, assist in drafting of manuscripts, present research at conferences. Optional: Assist in lecturing a graduate level course in cavity optomechanics. Minimum Qualifications
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protocols as dictated by experimental results. May assist with supervision of laboratory staff. Oversee maintenance of hazardous/chemical waste records and disposal as needed. Knowledge, Skills & Abilities
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-reviewed journals, books or chapter publications. Participate or present at meetings and conferences. May co-author and may co-present results with principal investigators at meetings or conferences. Assist
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appropriate. Assist with preparation of grants from the lab. Remain updated on the literature of the related research topic and develop the project aligned with the PI's research focus. Plan, coordinate, and
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applications, and preparing progress reports. Develop and implement protocols as dictated by experimental results. May assist with supervision of laboratory staff. Oversee maintenance of hazardous/chemical waste
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networks in the heart with the goal of developing methods for the early diagnosis of heart disease as well as novel treatment options by employing state-of-the-art computational approaches. The ideal