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Associate or Full Professor, tenure-track (Health Data Science)

Employer
Brown University School of Public Health
Location
Providence, Rhode Island
Salary
Commensurate with experience
Date posted
Dec 22, 2022

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The Brown University School of Public Health is pleased to announce a school-wide opening for an Associate or Full Professor with emphasis in Health Data Science. This interdisciplinary position will have a primary appointment in one of the four departments in the school (Behavioral and Social Sciences, Biostatistics, Epidemiology, or Health Services, Policy, and Practice) and will join a growing and vibrant faculty. In this global search, we are seeking candidates with demonstrated ability for innovative, high impact research in health data science, broadly defined, classroom teaching, and student advising and mentoring.  

This search will take a broad view of data science research. Areas of interest include, but are not limited to, statistical and data-analytic methodology, health information systems, machine learning, text mining, societal impact of artificial intelligence, algorithmic fairness in health, multimodal data modeling, data-driven policy evaluation and decision making, and data integration. The School of Public Health and the broader University offer opportunities for substantial collaboration with world class researchers in many areas of data science and in a broad range of domain areas, such as health care and policy research, technology assessment, brain sciences, computational biology, alcohol and addiction research, and gerontology.  

The School’s educational programs are responsible for teaching a growing number of students at the undergraduate, Master’s, and PhD levels. More information about the educational and training functions of the School is found at https://www.brown.edu/academics/public-health/academics

Minimum requirements: Candidates must have a doctoral degree in a constituent field of public health, or in a methodologic field such as (bio)statistics, epidemiology, computer science, operations research, industrial engineering, applied mathematics, or economics.  The candidate must have demonstrated excellence in innovative and high-impact research in data science (broadly defined) and in classroom teaching and student advising, and have interest and demonstrated ability for engaging in interdisciplinary public health research. All candidates must show evidence of excellent oral and written communication skills and a commitment to fostering and maintaining an inclusive, diverse and equitable educational environment. The School of Public Health is strongly committed to the principles and goals of the Brown University Pathways to Diversity and Inclusion initiative (https://diap.brown.edu/plans-reports).

Please apply online at http://apply.interfolio.com/98685. Review of new applications will begin on April 1, 2023.  Full consideration will be given to all applications received by that date. Applications received after the priority deadline may be reviewed until the position is filled or the search is closed.

Interested applicants should submit a letter of application, curriculum vitae, 2 best papers of relevance to the call, and diversity statement through Interfolio. The letter of application should include a teaching statement, a research statement, a description of the applicant’s contributions to data science, and the department with which they affiliate most closely.  Brown University is committed to increasing diversity and inclusion of underrepresented groups. In your diversity statement, please address how your past and present work demonstrates a commitment to diversity, equity, and inclusion, and how you intend to continue your commitment to diversity in future work. We value the different ways this might be demonstrated through scholarship, teaching, mentoring, service, and community engagement.

As an EEO/AA employer, Brown University provides equal opportunity and prohibits discrimination, harassment and retaliation based upon a person’s race, color, religion, sex, age, national or ethnic origin, disability, veteran status, sexual orientation, gender identity, gender expression, or any other characteristic protected under applicable law, and caste, which is protected by our University policies.

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