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, epigenomics, transcriptomics, and proteomics) information. The postdoctoral fellow will develop and refine machine learning methods for analyzing histopathology, clinical, and multi-omics data, collaborate with
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. Please include its goals, methods, and potential impact. Discussion of how your work connects to the themes of the Research & Design Studio, particularly around the ethical and political dimensions
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, using an array of methods including natural language processing and experiments. This is a two-year position (one-year contract renewable based on performance). The primary criterion for acceptance is
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. Additional Qualifications Attention to detail and professionalism are highly important for the role. Experience with participant recruitment and retention methods. CITI certified and trained in Good Clinical
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of Massachusetts would be a plus but not required. Attention to detail and professionalism are highly important for the role. Experience with participant recruitment and retention methods. CITI certified and trained
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training experience will provide: A strong foundation in research design, methods, and analytic techniques appropriate to the proposed research; An enhanced ability to conceptualize and think through
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of private-sector data to understand disparate impacts in the recent economic recession and recovery. Much of the team's ongoing research uses quasi-experimental methods to identify causal effects and test the
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University of California, San Diego (Scripps Oceanography), laboratory of Farooq Azam Korinna Kunde, Ph.D. In the Iron Continuum: Physicochemical Metal Speciation Dictates Bioavailability University
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important for the role. Experience with participant recruitment and retention methods. CITI certified and trained in Good Clinical Practice. REDCap, data collection and data entry experience also preferred
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with participant recruitment and retention methods. CITI certified and trained in Good Clinical Practice. REDCap, data collection and data entry experience also preferred. Contact Information: Mark