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are considered . Please apply by uploading a single PDF file that contains the following: Cover/Motivation Letter that discuss your fit for the position (1 page). Detailed CV A research statement that discusses
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, and contact information for three references directly to Professor Xiaolu Yang at [email protected] . The cover letter should briefly describe your research interests, key skills, and
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-related data, with a focus on longitudinal data analysis, population databases, and causal inference. This project has two components: The re-contacting of 507 Utah-based participants in the NICHD ENDO
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implementation, literature reviews, data collection and management, qualitative and quantitative data analysis, development and evaluation of research measures, interpretation of research findings, and
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 2 hours ago
. The successful applicant will develop physics-based and empirical models for uncertainty in acoustic propagation and validate them with existing ocean acoustic data sets. This position is fully funded for two
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Requirements Standing or sitting up to 8 hours/day, lifting <30 lbs, may view computer up to 8 hours/day. Shift Generally Monday – Friday, 8a-5p with some flexibility Job Summary This position is designed
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Instructions to Applicant Please submit the following materials as part of your application: Current Curriculum Vitae (CV). Cover letter. Contact information for three professional references. Notice
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cover letter (describing research experience, research interests, long-term career goals, and available start date), a CV, and contact information for three references. Baylor College of Medicine
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and Staff Positions , Search #499840 to upload a resume, cover letter, and contact information for three (3) professional references. Applicants must clearly demonstrate how they meet the stated minimum
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data and deep learning methods to assess canopy cover, quality, carbon stocks, and ecosystem services. Mandatory requirements: PhD in areas related to forest resources, remote sensing, data science, or