The Department of Management Science and Statistics at UTSA, in collaboration with The Department of Anesthesiology at UT Health SA, is accepting applications for a postdoctoral fellow position on optimal provider scheduling for healthcare clinical operations.
The successful candidate will be part of a collaborative research project to develop of optimal solutions for the scheduling of healthcare operations in a hospital system, which has been challenged with new clinical uncertainties created by the COVID-19 pandemic in critical care, complex surgical cases, as well as, ambulatory surgical procedures.
The initial appointment is for one year, starting as soon as possible. The renewal of the appointment for a second year will depend on mutual consent, satisfactory performance, and funding availability.
The successful candidate will lead research activities, including developing models and algorithms, and be willing to present findings to local, national, and international audiences.
Qualifications: Applicants must hold a Ph.D. in a relevant field such as management sciences, industrial engineering, operational research, data analytics, or machine learning. Be able to demonstrate merits and strong scientific publications in relevant fields. Possess strong research skills relevant to optimization, data analytics, decision-making under uncertainty, and healthcare. Be proficient in English, both spoken and written. Possess team working abilities.
A candidate with extensive knowledge of scheduling, optimization, healthcare operations, resource management, and stochastic processes is desirable. Experience in industry-academic partnerships is preferred.
Application details:
Interested individuals should submit an application package via the STARS application portal (click here). For questions, please contact Kimberly.Kyle@utsa.edu. The application package should include:
- A cover letter including a brief statement of research interests and motivation for the position,
- Curriculum Vitae (CV) including a list of publications and research projects,
- Samples (max 3) of originally authored research publications and/or technical reports relevant to the position,
- Names and contact information for three persons willing to act as references, and
- Any other information relevant for the position, such as a description of software development experience, or previous industry experience.
The review of applications will begin immediately and continue until the position is filled. To receive full consideration, please submit your application material as soon as possible, but no later than September 11, 2020.
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Arkajyoti Roy
Assistant Professor
The University of Texas at San Antonio
San Antonio TX
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