-
disparities for communities and populations. Candidates will receive mentorship and training in precision health, including advanced statistical methods focused on predictive modeling in relation to response
-
well as testing effectiveness of implementation supports (e.g., professional learning communities and coaching). Responsibilities: Coordinating data collection and analysis activities. Developing and disseminating
-
Communicate results through peer-reviewed publications, internal and external presentations, conferences, and websites. Minimum Requirements: Doctoral degree in a quantitative discipline such as computer
-
their communications Data Collection and Analysis: Collect data on the implementation process, including facilitator performance and participant feedback Analyze fidelity data to identify areas where
-
(e.g., Python, R, Julia) Excellent written and spoken communication skills A demonstrated ability to produce high-quality, peer-reviewed research Position Details: This position will remain open until
-
commonly used scientific scripting languages (e.g., Python, SQL, or R). We also seek candidates with good communication skills in spoken and written English, and an ability to produce state-of-the art
-
well as grow their scientific communication skills by writing scientific articles (research publications and reviews), presenting their work at UVA seminars and external conferences, and applying for funding
-
disorders. Communicate findings to the scientific community through conference presentations and publications. Preferred Qualifications: PhD in Computational Biology, Bioinformatics, Genetics, or a related
-
Markazyan, Academic Recruiter at ym3mm@virginia.edu For more information about UVA and the Charlottesville community please see http://www.virginia.edu/life/charlottesville and https://embarkcva.com
-
· Effective written and verbal communication skills. · PhD degree in computer science, data science, or related fields, to be completed by the start date of the appointment. · Strong software