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Primary Responsibilities: Lead and contribute to experimental design, data collection, analysis, and manuscript preparation Mentor and supervise undergraduate and graduate research assistants Support the
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. Particular emphasis to be placed on developing and applying emergent system identification and modal decomposition techniques as well as statistical analysis of large datasets. Candidate will disseminate
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. This position offers a unique opportunity to join a world-class team dedicated to understanding and advancing the field of cancer immunology through innovative spatial analysis of the tumor microenvironment
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analytical methods and make recommendations for utilization; assists in establishment of controls, criteria and research standards; performs critical analysis of literature relevant to research being
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, magnetic resonance imaging, nuclear medicine, etc.; develops AI models for medical image synthesis and virtual clinical trial; plans, coordinates and oversees processing and analysis of data; analyzes and
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expertise in educational and social science research methods, with a strong background in quantitative and/or qualitative analysis. Show evidence of experience in survey research, instrument development, and
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quantitative analysis, including management of behavioral and cognitive measures. Direct implementation of the AquOTic therapeutic protocol, delivering weekly evidence-based aquOTic sessions and conducting
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, geochemistry, and molecular microbiology and genomic analysis. Demonstrated experience measuring rates of microbial processes, and other microbiology laboratory equipment is required. Other required skills
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following qualifications and experiences: Experience with developing or applying ecosystem models (e.g., SWAT-Carbon, CLM, EPIC, DNDC, and DayCent) Experience with analysis of geospatial data and time series
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assistant will support the delivery of program interventions, assist with pre- and post-data collection through in-person and electronic reminders and assist with initial review and analysis of de-identified