RESEARCH FACULTY FELLOW FOR CLEMSON CENTER FOR PUBLIC HEALTH MODELING AND RESPONSE
Title: Research Assistant Professor
Location: Department of Public Health Sciences (Clemson University’s main campus, SC)
Term: renewable 12-month position
Start date: August 1, 2023 (negotiable)

Clemson University’s Center for Public Health Modeling and Response (PHMR) invites applications for Clemson University’s Research Faculty Fellow in dynamic modeling and prediction.

The mission of PHMR is to develop and utilize data-driven approaches to inform clinical and public health decision-making and assist the ability of health organizations and communities to prepare for, and respond to, public health threats. We are seeking individuals with expertise in Bayesian approaches, Markov chain models, machine learning techniques, or dynamic compartmental or agent-based modeling. We will also consider highly motivated individuals who are interested in transitioning into these fields.

Duties and responsibilities:

• Development and implementation of statistical, mathematical, or machine learning techniques to support research and implementation projects across campus

• Development of novel methodology and software packages in settings where existing prediction techniques underperform

• Assist or lead manuscript development in public health, medical, and related fields. In addition, the Research Faculty Fellow may be expected to lead manuscripts in statistical, mathematical, or machine learning methodology journals.

• CU Research Faculty Fellow will be provided with the opportunity to assist in planning and development of externally funded proposals, or lead their own proposals

• CU Research Faculty Fellow will have doctoral student and postdoc support

• Provide doctoral student mentoring or faculty consultation in data analysis and/or prediction. Research Faculty Fellow will be expected to hold office hours 2x per week.

Project applications are in epidemic, pandemic, and disaster modeling, but the Research Faculty Fellow will have the opportunity to choose additional projects. PHMR’s main projects include 1) Newly funded NIH R01: Developing a dynamic modeling framework for surveillance, prediction, and real-time resource allocation to reduce health disparities during Covid-19 and future pandemics (PI: Rennert). The main areas of focus are A) development and implementation statistical models to estimate infectious disease transmission dynamics and disease prevalence and B) development and implementation predictive modeling frameworks to predict infectious disease trajectories and allocate resources (via Bayesian statistical models, machine learning, or mathematical models such as compartment-based or agent-based models). 2) Data-driven approaches to identify communities at high risk of opioid overdose, hepatitis C virus (HCV), and human immunodeficiency virus (HIV) for prioritization of mobile health clinics and other emergency support. This project, funded by the SC Center for Rural and Primary Health Care, is a correlate of project 1. 3) Development of wastewater prediction models for early detection of disease outbreaks. This project is also related to projects 1 and 2. The candidate will have the option to work on all projects simultaneously.

Supervision
The Research Faculty Fellow’s main appointment will be within the Center for Public Health modeling and Response, located within the Department of Public Health Sciences. Dr. Rennert as the primary advisor. The Fellow will also work closely with (bio)statisticians and epidemiologists from Clemson University’s School of Mathematical and Statistical Sciences and University of San Diego’s Division of Infectious Disease and Global Public Health. The appointment if funded for 2 years, with future years contingent on funding/performance. Salary is highly competitive (and negotiable) with a competitive benefits package and negotiable start date.

The candidate must be highly motivated with a PhD in statistics, biostatistics, epidemiology, computer science, or a related quantitative field. Experience with statistical prediction, Bayesian approaches, mathematical modeling, or machine learning are desired. Solid coding experience in R, CPlusPlus, Python, or a related software package is essential.

Applicants should submit a cover letter, CV, and contact information for three references through Interfolio: insert link here Inquiries should be sent to Dr. Lior Rennert (liorr@clemson.edu). The application deadline is May 1st, 2023.