Assistant, Associate or Full Professor, Public Health Data Science and Data Equity
Assistant, Associate or Full Professor, Public Health Data Science and Data Equity
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Job Description
The School of Public Health at Yale University (YSPH) is seeking applicants at the rank of Assistant Associate or Full Professor on the Tenure Track for the new schoolwide Public Health Data Science and Data Equity Initiative. The home department within YSPH will be decided based on the candidates expertise and background. We are particularly interested in applicants with demonstrated records of conducting cutting-edge research in public health data science. Areas of interest include but are not limited to data science methods in electronic medical records causal inference digital health real-world healthcare data climate change infectious diseases public health genetics/genomics healthcare policy data science for global health large-scale data integration machine learning (ML) and artificial intelligence (AI) fairness ethics in AI/ML and high-performance statistical computing.
As one of the first schools of public health in the nation YSPH has a rich history of being at the forefront of innovative research and education. YSPH serves local national and international communities through its high impact interdisciplinary research and training of a diverse group of masters and doctoral students. We believe that the future of public health will be defined by four pillars: inclusivity innovation and entrepreneurship communication and data-driven leadership.
Responsibilities
The successful candidate will be expected to:
Develop and maintain an active externally funded independent research program focused on development of innovative data science methodology in a specific/broad area of public health.
Take a leading role in further developing methodological research in data science and engage in collaborative research.
Work to strengthen equity and fairness in public health data science.
Publish and present research results in peer-reviewed professional journals and at scientific conferences garnering national and international visibility.
Contribute to the data science education program through teaching at least one course at the masters/doctoral level each year and mentoring students.
Provide service to the department school and university through committee work participation in events etc.
For additional information about YSPH please visit doctoral degree in Biostatistics Statistics Epidemiology Computer Science Data Science Informatics or a related field by the start of appointment. We envision that along with being rooted in traditional quantitative disciplines a non-traditional data science scholar with a quantitative degree and expertise but focusing on a substantive area such as environmental exposure modeling or healthcare policy will be well-suited for this opening. As mentioned the home department (within YSPH) will be chosen based on the best fit for the background and expertise of the candidate. For additional information about YSPH please visit Experience: IC
Employment Type
Full Time
Key Skills
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