The Department of Health Policy and Management (HPM) at the Johns Hopkins Bloomberg School of Public Health (BSPH) invites applications for a tenure track assistant professor to join in cutting-edge research and development related to data science and computer science applied to the fields of population health, health care delivery systems, health policy, and risk stratification/prediction. A special emphasis of this position is on the application of predictive modeling and artificial intelligence using electronic health records and insurance claims to address analytic bias and health disparities in predicting healthcare utilization.
Faculty hired through this search will be a core faculty of the Johns Hopkins Center for Population Health IT (CPHIT) and have an opportunity to affiliate with any of the Department’s Centers and Institutes, and Affiliated Programs, in support of their research and practice activities. The goal of CPHIT is to undertake research and development that melds the intellectual assets of our globally leading university to develop important health IT/informatics/data science-based applications for public health agencies and the health care industry. Although CPHIT is housed in HPM, faculty members at CPHIT collaborate closely with otherdepartments at JHU such as the Department of Biostatistics at the Bloomberg School, Computer Science at the School of Engineering (e.g., Malone Center), the Biomedical Informatics and Data Science (BIDS) at the School of Medicine, the Applied Physics Laboratory (APL), and the school-wide inHealth initiative. CPHITalso collaborates very closely with the Johns Hopkins Health System and severalother leading integrated delivery systems and government health agencies.
The faculty member will have the opportunity to participate in the research and development activities of the Johns Hopkins ACG® Population Health Analytics Project. JH-ACGs is one of the largest university-based technology transfer activities of its type in the U.S. and leads to rapid translation of CPHIT-led research to positive analytic impact around the globe. The JH-ACG’s research and development team is an international leader in health care risk adjustment and advanced predictive analytics. JH-ACG solution is an advanced population focused predictive analytics software tool applied in 25+ nations to manage the care of over 250+ million patients based on digital health care data sources.
Candidates should have a PhD, ScD, DrPH, MD, or comparable degree in computer science or a closely relevant field with advanced training and experience in artificial intelligence (AI), machine learning (ML), or Natural Language Processing (NLP). Experience and/or career interest in working within multi-disciplinary, population health, community health, and health services research/delivery system environments is required. Special interest in issues associated with algorithmic bias of AI and other predictive models, and its effect on health care disparities and inequities is preferred. Familiarity with the U.S. health care or public health systemis also preferred.
Candidates should have an established track record of externally funded research or a strong research portfolio that can be supported by external grants and contracts. The successful candidate will be expected to teach graduate level courses, and must demonstrate a commitment to graduate-level advising, mentoring, and teaching excellence.
This is an exciting time to join HPM and BSPH. HPM is one of the Bloomberg School’s ten departments and one of the largest in the country. The Department is dedicated to advancing local, national, and federal health policy to make a difference. BSPH was ranked #1 in HPM by peers in the 2023-2024 U.S. News & World Report. HPM is chaired by Dr. Keshia Pollack Porter. As chair, she is advancing a bold vision regarding scholarship, education, practice, and policy impact. Under her leadership, the Department has reaffirmed its committed to advancing inclusion, diversity, anti-racism, and equity (IDARE) in scholarship, education, practice, and the department’s culture.
There is also excitement for AI and data sciences at the University. JHU is in the process of rolling out a globally leading campus-wide initiative in the application of AI and data science to a wide range of disciplines (https://ai.jhu.edu). JHU also has many advanced high performance data platforms and is a global leader in the application of advanced computer technologies (https://www.idies.jhu.edu). Thisposition represents a unique opportunity to gain experience working within one of the largest and most highly regarded research universities in the world. Careeradvancement within the faculty ranks is actively supported for all new faculty hires.
Applications are due by 11:59 PM ET on 4/30/24. The ideal position start date is January 2025; however, the starting date can be flexible. This position is seeking someone at the assistant professor level; however, depending on candidate qualifications, an appointment at the associate professor may be considered.
Applicants should submit a letter of interest, a job market paper or publication reflective of their research, and current CV tohttps://apply.interfolio.com/142759 , which is the University’s secure online search platform. Applications should include a statement of demonstrated commitment to the principles of inclusion, diversity, anti-racism, and equity (IDARE) in scholarship, teaching, policy, and/or practice, and ways to continue to uplift these principles as a member of the HPM faculty (statement may be included in the cover letter or as a separate document).
Two confidential reference letters are required for applicants who have completed their degree within two years. These letters should be directly submitted by referees through Interfolio. Other candidates should submit the names of three references as part of their initial application.
Cover letters should be addressed to the Search Committee Chair, Jonathan Weiner, a professor in HPM and director of CPHIT. Please direct all questions about this search to Ms. Edith Jones, Senior Administrative Coordinator, at ejones10@jhu.edu.
The Johns Hopkins University is committed to equal opportunity for its faculty, staff, and students. To that end, the university does not discriminate on the basis of sex, gender, marital status, pregnancy, race, color, ethnicity, national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status or other legally protected characteristic. The university is committed to providing qualified individuals access to all academic and employment programs, benefits, and activities based on demonstrated ability, performance, and merit without regard to personal factors that are irrelevant to the program involved. All applicants who share this goal are encouraged to apply.