Assistant, Associate or Full Professor, Public Health Data Science and Data Equity

New Haven, CT

Yale University

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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 candidate’s 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 master’s 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.

·       Have an interest in strengthening 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 http://publichealth.yale.edu/.

Qualifications

  • A 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.
  • Excellent oral and written communication skills and the ability to work effectively with a wide range of constituencies in a complex and diverse community.
  • Proficiency with statistical computing (e.g., R, Python or C/C ).
  • Interest and expertise in large-scale data management, linkage and data integration.
  • Demonstrated capacity to work both collaboratively and independently.

 

For additional information about YSPH please visit http://publichealth.yale.edu/.

Application Instructions

Review of applications will begin immediately and will continue until a successful candidate is identified.

Applicants are asked to upload (1) a cover letter that addresses research/professional accomplishments/ interests, (2) curriculum vitae, (3) a teaching statement that includes teaching philosophy and experience, (4) a statement of research/professional accomplishments and interests, (5) the names and contact information for three references.

 

Questions regarding this position should be directed to:  admin.dsdeysph@yale.edu

 

 

 

 

Equal Employment Opportunity Statement

Yale University is an Affirmative Action/Equal Opportunity employer. Yale values diversity among its students, staff, and faculty and strongly welcomes applications from women, persons with disabilities, protected veterans, and underrepresented minorities.

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Category: Research Jobs

Tags: Biostatistics Causal inference Computer Science Data management Machine Learning Python R Research Statistics Teaching

Perks/benefits: Career development Conferences

Region: North America
Country: United States

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