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opportunities to collaborate across Indiana University’s aging research network. Projects are clinically motivated and span mixed methods intervention development, usability testing, implementation research, and
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to national, professional meetings for possible presentations. Expected to publish in peer reviewed journals. Basic Qualifications EDUCATION Required Doctorate degree (PhD) in science or related field SKILLS
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include the Society for Maternal-Fetal Medicine (SMFM) Annual Meeting and the North American Fetal Therapy Network (NAFTNET) Fall meeting. Skills: Proficiency in statistical analysis and experience using
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of quantum algorithms for hybrid quantum simulators. Applicants should have a PhD in Physics, Chemistry, Computer Science, or a closely related field. To apply, a CV, a brief statement of research interests
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opportunities for collaboration with Michigan State University, and IU’s network in cognitive modeling, AI, and human–AI decision research. This postdoctoral appointment is full-time and on-campus. Job Duties 80
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leading role in the synthesis of network observations, including forest inventory data (e.g. from the USDA Forest Inventory and Analysis program) and flux tower data (e.g. from AmeriFlux and FLUXNET
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opportunities for collaboration with Michigan State University, the Milwaukee Police Department Academy, and IU’s network in cognitive modeling, AI, and human–AI decision research. This postdoctoral appointment
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hold a PhD in an area related to mineralized tissue research. Candidates must have a sound research background in inorganic chemistry and materials science with a strong understanding of hydroxyapatite
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of quantum algorithms for hybrid quantum simulators. Applicants should have a PhD in Physics, Chemistry, Computer Science, or a closely related field. To apply, a CV, a brief statement of research interests
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scales. The successful candidate will play a leading role in data analysis and software development. A Ph.D. in experimental high-energy or nuclear physics is required by time of appointment. No prior