Postdoctoral Scholar - Public Health Sciences

## Postdoctoral Scholar - Public Health Sciences Apply locations:
College of Medicine time type:
Full time posted on:
Posted Todayjob requisition :
REQ #
** APPLICATION INSTRUCTIONS:*** ## CURRENT PENN STATE EMPLOYEE (faculty, staff, technical service, or student), please login to Workday to complete the internal application process. Please do not apply here, apply internally through Workday.* ## CURRENT PENN STATE STUDENT (not employed previously at the university) and seeking employment with Penn State, please login to Workday to complete the student application process. Please do not apply here, apply internally through Workday.
* ## If you are NOT a current employee or student, please click “Apply” and complete the application process for external applicants.
** Approval of remote and hybrid work is not guaranteed regardless of work location. For additional information on remote work at Penn State, see Notice to Out of State Applicants.
** 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.
** POSITION SPECIFICS
** The Department of Public Health Sciences (PHS) seeks a highly motivated Postdoctoral Scholar to contribute to research in nutritional epidemiology, chronic disease prevention, and the generation of real-world evidence using large real-world data sources, including data from the ongoing prospective cohort study (DREAM cohort). The successful candidate will have expertise in epidemiologic research methods, experience working with complex real-world datasets, and strong quantitative and analytical skills.

This position offers opportunities to collaborate on interdisciplinary research projects, develop independent research expertise, and contribute to high-impact publications and grant-funded research.
** PRIMARY DUTIES AND RESPONSIBILITIES
*** Design and conduct epidemiologic studies using multiple data sources.
* Develop research protocols, statistical analysis plans, graphical displays, and other study-related documents.
* Perform advanced statistical analyses using large epidemiologic, clinical, and administrative datasets.
* Prepare manuscripts for publication in peer-reviewed journals.
* Contribute to grant writing and the development of research funding applications.
* Present research findings at scientific meetings and conferences.
* Collaborate with faculty investigators, research staff, and trainees on ongoing research projects.
* Participate in other scholarly activities that support the Department's research mission.
** REQUIRED QUALIFICATIONS
*** Doctoral degree (PhD, DrPH, ScD, or equivalent) in Epidemiology, Nutrition, Biostatistics, or a related field.
* Training and experience in epidemiologic research methods.
* Experience working with large real-world datasets including electronic health records (e.g., TriNetX), claims databases (e.g., Market Scan), or survey datasets (e.g., NHANES).
* Demonstrated experience designing epidemiologic studies and developing research protocols.
* Demonstrated experience conducting advanced statistical analyses using SAS and R; familiarity with Mplus is preferred.
* Experience supporting the preparation of scientific manuscripts for peer-reviewed publication and assisting with the development and writing of grant proposals.
* Strong analytical, organizational, written, and verbal communication skills.
* Demonstrated ability to work both independently and collaboratively in a multidisciplinary research environment.
* Commitment to rigorous scientific methodology, research integrity, and ethical conduct of research.
** PREFERRED QUALIFICATIONS
*** Expertise in nutritional epidemiology and diet-related chronic disease research.
* Experience with causal inference methods, longitudinal data analysis, and advanced epidemiologic methods.
* Experience developing and analyzing dietary patterns derived from Food Frequency Questionnaires (FFQ), including dietary quality indices and data-driven approaches such as principal component analysis, factor analysis, or related methods.
* Experience working with dietary…