12 big-data-and-machine-learning-phd Postdoctoral research jobs at University of Massachusetts
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of Information & Computer Sciences About UMass Amherst The flagship of the Commonwealth, the University of Massachusetts Amherst is a nationally ranked public land-grant research university that seeks to expand
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Apply now Job no:525134 Work type:Post Doc (Amherst Only) Location:UMass Amherst Department: Elect & Computer Engineering Union: Post Doc Categories:Postdoctoral Research Associate, College
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field. Strong foundational knowledge in participatory research and social sciences methods. Strong experience working with large datasets (ideally, but not required, with fisheries, socioeconomics data
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cooperative working relationships with coworkers, students and collaborators. Organizational skills to effectively manage and maintain large data sets. High level of independence and reliability. Demonstrated
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resources and warming climate. The ideal candidate will have highly developed skills in any of the following areas: hydrologic and/or water resources modeling, data science and machine learning with strong
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skills, data management and analysis experience, problem solving skills, the ability and willingness to lead and organize a large research effort, and will work productively and enthusiastically with
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well with a diversity of faculty, staff, and students from a variety of disciplines within and outside the University. Excellent computer skills, including Excel and Word, and the ability to learn new
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skills. Physical Demands/Working Conditions Standard office - ability to sit in front of a computer for an extended period of time. Ability to complete fieldwork including mark-resighting efforts which
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containing updated data and calculations pertaining to the GHG inventory implications of the land uses and practices analyzed over the course of the project, as well as relevant recommendations that can
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research focused on LGBTQIA+ youth mental health. The Postdoctoral Research Associate responsibilities will include assisting Dr. Goff and the research team in quantitative and qualitative data collection