98 software-engineering-model-driven-engineering-phd-position Fellowship positions at Zintellect
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Microsoft Office applications and familiarity with statistical analysis methods and software. Critical thinking and scientific judgment to evaluate complex environmental health data and site conditions to
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surveillance initiatives. Laboratory data-management skills: You will learn to operate various instrument software and a laboratory management database for analytical result review, laboratory information
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practical experience in data analysis, scientific writing, oral presentations, project planning, and working on multi-disciplinary teams. Experience conducting statistical analyses with statistical software
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established software tools, with opportunities to explore and evaluate emerging analytical approaches. Gain experience measuring physiological responses to root treatments and characterizing plant traits
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reviews, statistical programming and analysis using software such as SAS, SUDAAN, and R, data interpretation and visualization, scientific writing, and scientific communication. You will also develop skills
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sequencing) Familiarity with statistical analysis or bioinformatic software (R, Python, QIIME2, BLAST-based workflows etc.). Scientific writing (i.e. thesis chapters, manuscripts.) Stipend $74,678.00 Yearly
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, COMPASS-31 measures, etc. The project may include descriptive analysis, multivariable modeling, and integration of findings across epidemiologic datasets to improve understanding of infection-associated
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modeling techniques to identify patterns, trends, and emerging public health concerns. Design and evaluation of interactive data visualizations and dashboards to communicate scientific findings. Best
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Young, PhD, MPH ([email protected] ). If you have questions about the nature of this opportunity, please contact the mentor(s). Anticipated Appointment Start Date: September 13, 2026. Start date is flexible
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, or related data manipulation and analysis software Strong scientific and technical writing skills Experience with analyzing complex surveys, developing cohort analyses, and testing health outcomes in cross