Department: Phar Health Outcomes & Policy

Salary: Commensurate with experience

Description:

The University of Houston (UH) College of Pharmacy invites qualified candidates to apply for a full-time, tenure-track Presidential Frontier Faculty position at the rank of assistant or associate professor in the Department of Pharmaceutical Health Outcomes and Policy (PHOP). The Presidential Frontier Faculty program is a university-wide integrated interdisciplinary hiring campaign that is overseen by central university leadership and encompasses hiring a large cohort of convergence research faculty to work on health, energy, sustainability, and security.

The UH is a Carnegie-Designated Tier 1 public research university and a member institution of the world-renowned Texas Medical Center, which houses major academic research programs in cancer, genetics, and neuroscience with a significant focus on translational research. With over 46,000 students, UH offers a comprehensive range of programs across 15 colleges, fostering innovation in fields such as energy, health, hospitality, business, education, law, STEM, and the humanities. Boasting top-tier faculty, state-of-the-art facilities, student success initiatives, and a strong commitment to community engagement, UH prepares students to thrive in a globally interconnected world while contributing impactful research and innovation to the region and beyond.

All applicants must hold an earned Ph.D. in health outcomes or closely related health analytics disciplines with a strong background in data science. Applicants must have peer-reviewed publications involving Artificial intelligence (AI) and machine learning (ML) methods in healthcare. The successful candidate will be expected to develop a sustainable independent research portfolio, teach in the PharmD and graduate programs, and mentor PhD students. The candidate will join an active research and teaching program. The Department of Pharmaceutical Health Outcomes and Policy consists of eleven core faculty members and is supported by two administrative support positions. Currently, there are 20+ PhD students in the PHOP graduate program. Considerable opportunities for research collaboration also exist across the university campus and institutions in the Texas Medical Center. This position will work closely with the Center for Population Health Outcomes and Pharmacoepidemiology Education and Research (P-HOPER Center). A competitive applicant will be able to contribute to the P-HOPER Center’s mission to improve population health outcomes through innovative research, education, and practices.

The University of Houston welcomes candidates whose experience in teaching, research, or community service has prepared them to contribute to our commitment to excellence. Applications will be accepted until the position is filled, although an early application is recommended. Screening will begin immediately and continue until the position is filled. Rank, salary, and start-up package will be commensurate with qualifications and experience. Interested individuals should electronically submit a cover letter, a statement of research interest, a statement of teaching philosophy, a curriculum vitae, and the names of three references with detailed contact information to:

Please visit https://uh.edu/provost/faculty/faculty-resources/prospective-faculty/ to apply.

Any questions may be addressed to Dr. Hua Chen, Search Committee Chair, Phone: (832) 842-8355, E-mail: hchen20@uh.edu 

Additional information is available on the University (http://www.uh.edu), the Department (http://www.uh.edu/pharmacy/about-us/academic-depts/phop/), and the P-HOPER Center https://uh.edu/pharmacy/research/centers-and-institutes/p-hoper-center/

The University of Houston is responsive to the needs of dual career couples.

Qualifications:
All applicants must hold an earned Ph.D. in health outcomes or closely related health analytics disciplines with a strong background in data science. Applicants must have peer-reviewed publications involving Artificial intelligence (AI) and machine learning (ML) methods in healthcare.

Required Attachments by Candidate:
Cover Letter/Letter of Application, Teaching Philosophy or Statement, Research Statement, Curriculum Vitae

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