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materials:1) a cover letter of application2) a curriculum vitae3) a sample of writing in the candidate's field of specialization4) contact information for three or more references Applications received by
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closely-related field. Applicants should include a cover letter, a curriculum vitae including a publication list, and contact information for three references by applying on the Princeton University
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at Princeton University.To apply online, please visit https://www.princeton.edu/acad-positions/position/37121 and submit a cover letter, CV, Research Statement, Publication list and contact information
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required.Applicants must apply online and submit a CV, a 3-5 page (double-spaced) statement of research interest/research proposal, a writing sample, and the names of two (and not more than two) references. A cover
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data-driven, computational approaches. Successful candidates will be willing and able to work across a breadth of disciplines - from genomics to computer science, sociology to psychology, engineering to
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://puwebp.princeton.edu/AcadHire/position/39603 and submit a cover letter, C.V., one or at most two research papers, and three reference letters. This position is subject to the University's background check policy
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).How to ApplyApplicants should submit a CV, contact information for three references, and a cover letter describing their areas of expertise and interest. References may be contacted for candidates who
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/acad-positions/position/38061and submit a CV (including a list of publications), brief cover letter (summarizing prior research experiences and future interests), and contact information for two
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should include a cover letter, a curriculum vitae including a publication list, a 1-2 page statement of research interests and goals, and name, address and email address of three referees familiar with
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Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning
learning. Our previous work has demonstrated that neural networks can skillfully predict sea ice data assimilation increments, which represent structural model errors (https://doi.org/10.1029/2023MS003757