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at the University of Texas, Austin (DHH Lab, PI: Kavita Radhakrishnan RN, PhD, MSEE FAAN FAHA) is seeking to fill a postdoctoral research position. Our lab is devoted to investigating the efficacy of current and
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School of Nursing (PI: Eun-Ok Im RN, PhD, MPH FAAN) is seeking to fill a postdoctoral research position. The post-doc fellow will assist in multiple NIH-funded studies on technology-based interventions
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yields Writing papers and reports Required Qualifications PhD in geology, geochemistry, material science, or chemical engineering. Demonstrated experience in conducting and interpreting laboratory
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Start Date: Immediately ---- Position Duration: Expected to Continue Until May 05, 2025 ---- Location: AUSTIN, TX ---- Job Details: General Notes PhD must have been received within the past 3 years
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Northwest, USA. Report results to stakeholders. Required Qualifications PhD in related field. Knowledge of quantitative characterization and interpretation of sedimentology/stratigraphy of continental margins
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, including overseeing data analysis and dissemination, and mentoring and training junior scholars, and grant writing. PhD in nursing, earned from a U.S. institution in the last three years Desire to pursue a
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. Develop and lead independent investigations under the direction of PI Schnarrs. Other related duties as assigned. Required Qualifications PhD degree in Human Development and Family Sciences, or related
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brainstorm ideas. Required Qualifications Completion of the doctorate prior to the start of the position is required. PhD must have been received within 3 years of the start date. Doctorate must be in health
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computational visualization. PhD must have been received within the past three years. The position is funded for a year with possibility of continuation based upon performance review, progress towards research
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collaboration with Georgia State University. Studies utilize task-based fMRI, memory task design, clinical interviews, social determinants of health, multimodal imaging, univariate, and multivariate statistical