CFA Postdoctoral Fellow - Center Pandemic Decision Science
Listed on 2025-12-19
-
Science
Data Scientist, Clinical Research
Job Posting Title
CFA Postdoctoral Fellow - Center for Pandemic Decision Science
Hiring DepartmentDepartment of Integrative Biology
Position Open ToAll Applicants
Weekly Scheduled Hours40
FLSA StatusExempt
Earliest Start DateImmediately
Position DurationExpected to Continue Until Oct 02 2026
LocationUT MAIN CAMPUS
General NotesThis is a one-year position with opportunity for renewal based on funding and performance. The position will include a full-time benefits package.
Security sensitive; criminal background check conducted on selected candidates. Hiring decision is contingent upon applicant clearing background requirement.
Applicants will be accepted on a rolling basis and evaluated via an accelerated video interview and decision process.
PurposeThe Meyers Lab and epiENGAGE at The University of Texas at Austin are immediately seeking outstanding postdoctoral scholars to contribute to modeling the spread, surveillance, forecasting, and control of influenza and other infectious diseases. The research aims to elucidate epidemiological dynamics and provide robust insights and tools to support outbreak preparedness and response efforts across the United States.
The postdoctoral scholars will work under the primary supervision and mentorship of Professor Lauren Ancel Meyers.
We seek candidates with strong quantitative training in one or more of the following areas: (1) modeling of infectious disease dynamics, (2) statistics, machine learning, and AI, or (3) operations research and optimization. Preference will be given to candidates with knowledge of infectious disease epidemiology.
Responsibilities- Lead the development and analysis of mathematical models to support the early detection, forecasting, and mitigation of emerging infectious disease outbreaks, including seasonal and pandemic influenza.
- Contribute to the development of outbreak modeling tools and training resources for public health professionals.
- Disseminate this work through direct engagement with scientists and public health professionals, as well as peer-reviewed publications.
Candidates must have completed a Ph.D. within the last three years in a quantitative science, statistics, computer science, mathematics, engineering, or a related discipline. The position will also require the ability to work quickly on time-sensitive analyses and collaborate with an interdisciplinary team.
Preferred QualificationsSeveral years of experience in designing, validating, and applying mathematical models of outbreak dynamics and control. Experience collaborating with communities and public health professionals.
Salary Range$70,000 + depending on qualifications
Working Conditions- Flexible work arrangement possible.
- Occasional evenings and weekends required.
- May work around standard office conditions.
- Repetitive use of a keyboard at a workstation.
- Flexible: 40 hours/week is required, and most of this time should be during normal business hours (e.g., 9:00 am – 5:00 pm), although numbers of hours/day and days/week can be negotiated and may change depending on what projects are being pursued.
- Resume/CV
- Cover Letter
- Three (3) letters of reference
- Ph.D. Verification (examples of official documentation of the degree).
The University of Texas at Austin, as an equal opportunity/affirmative action employer, complies with all applicable federal and state laws regarding nondiscrimination and affirmative action. The University is committed to a policy of equal opportunity for all persons and does not discriminate on the basis of race, color, national origin, age, marital status, sex, sexual orientation, gender identity, gender expression, disability, religion, or veteran status in employment, educational programs and activities, and admissions.
#J-18808-Ljbffr(If this job is in fact in your jurisdiction, then you may be using a Proxy or VPN to access this site, and to progress further, you should change your connectivity to another mobile device or PC).