Postdoctoral Scholar - Public Health Sciences

Penn State University • Tallahassee, FL

2d • Onsite

About The Position

The Department of Public Health Sciences, Division of Biostatistics and Bioinformatics, at Penn State College of Medicine in Hershey, PA invites applications for a Postdoctoral Scholar position in biostatistics, statistics, or a closely related quantitative field. The position will focus on the development of next-generation statistical methods and software for adaptive clinical trial designs, with an emphasis on early-phase oncology trials. The Postdoctoral Scholar will work under the mentorship of Dr. Shouhao Zhou at Penn State University, in collaboration with Dr. J. Jack Lee at MD Anderson Cancer Center and other clinical and methodological collaborators. The position provides an excellent opportunity for a highly motivated researcher to develop a strong independent research profile at the interface of Bayesian statistics, clinical trial design, optimization, computational statistics, and/or translational cancer research. The successful candidate will contribute to methodological innovation, computational implementation, simulation studies, software development, manuscript preparation, and grant-related research activities. The work will support ongoing and planned projects on Bayesian adaptive designs, globally optimal dose-finding and phase I/II designs, pediatric and adult oncology trials, and efficient optimization algorithms for complex trial design spaces. This is a term position; length of the term will be discussed during the interview process. Continuation past the term length discussed will be based on university need, performance, and/or availability of funding.

Requirements

• A PhD or equivalent doctoral degree in biostatistics, statistics, applied mathematics, operations research, computer science, engineering, or a closely related quantitative field.
• Strong programming skills in at least one major scientific computing language such as R, Python, C++, or a similar language.
• Ability to conduct independent research, communicate clearly, and work effectively in a multidisciplinary research environment.
• Strong written communication skills and interest in publishing methodological and collaborative research.

Nice To Haves

• Strong methodological training in statistical inference, computational statistics, reinforcement learning, or optimization.
• Experience with Bayesian statistics, adaptive clinical trial design, dose-finding methods, phase I/II trial designs, model-assisted or model-based trial designs, or oncology clinical trials.
• Prior publications or preprints in biostatistics, statistics, clinical trials, machine learning, optimization, or related methodological areas.
• Learning and applying deep learning, agentic AI, and other AI methods in assisting research is encouraged.

Responsibilities

• Contribute to methodological innovation
• Computational implementation
• Simulation studies
• Software development
• Manuscript preparation
• Grant-related research activities
• Support ongoing and planned projects on Bayesian adaptive designs, globally optimal dose-finding and phase I/II designs, pediatric and adult oncology trials, and efficient optimization algorithms for complex trial design spaces.

Benefits

• Competitive benefits package for full-time employees designed to support both personal and professional well-being.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree