Careers at UMass Amherst

UMass Amherst COVID-19 Response: The University of Massachusetts Amherst is currently re-examining open positions as our campus monitors and responds to the novel coronavirus pandemic. At this time, hiring priority is being given to positions that are critical to academic, research, and business continuity. Searches for current openings may be placed on hold or cancelled. Candidates will be contacted directly by the hiring department with regard to the status of their current application(s). We appreciate your patience and flexibility during these unprecedented times and thank you for your interest in the University of Massachusetts Amherst.

Postdoctoral Research Associate

Apply now Job no: 506573
Work type: Post Doc (Amherst Only)
Location: UMass Amherst
Department: Biostatistics & Epidemiology
Union: Post Doc
Categories: Postdoctoral Research Associate

About UMass Amherst

UMass Amherst, the Commonwealth's flagship campus, is a nationally ranked public research university offering a full range of undergraduate, graduate and professional degrees. The University sits on nearly 1,450-acres in the scenic Pioneer Valley of Western Massachusetts, and offers a rich cultural environment in a bucolic setting close to major urban centers. In addition, the University is part of the Five Colleges (including Amherst College, Hampshire College, Mount Holyoke College, and Smith College), which adds to the intellectual energy of the region.


Job Summary

The Postdoctoral researcher will be responsible for developing forecasting models for infectious diseases including COVID-19 and influenza, as well as ensemble methods to combine forecasts from multiple models. Researchers at the Reich Lab are leaders in this field; the lab is currently leading the COVID-19 Forecast Hub, a dynamic global collaborative research initiative (, and we have previously led similar initiatives for forecasting influenza. We have close collaborative relationships with many academic groups and public health agencies at the state and national level.


Essential Functions

  • Specific projects will be determined taking into account the Postdoctoral's interests and experience, and may be of either a methodological or an applied flavor. Possible topics include approaches to ensemble forecasting of novel pathogens; mechanistic models for forecasting disease progression or estimation strategies for such models; non-parametric time series forecasting models; models using hierarchical structure or copulas to capture dependence across time and space; and exploring the use of digital surveillance data to improve forecasts when the primary data source has reporting delays.
  • The successful candidate will be expected to write and submit academic manuscripts describing the results of this research.


Minimum Qualifications (Knowledge, Skills, Abilities, Education, Experience, Certifications, Licensure)

  • Strong quantitative background and formal training in statistics, machine learning, data science, computational epidemiology, or a closely related field.
  • Demonstrated proficiency with R or Python is required.
  • Doctoral Degree must be earned by time of appointment.


Physical Demands/Working Conditions

Typical office environment


Additional Details

Directly supervised by Dr. Nicholas Reich, Associate Professor


Work Schedule

M-F 40 hours per week


Salary Information

Pay is consistent with the bargaining unit contract.


Special Instructions to Applicants

Interested candidates should submit the following application materials for priority consideration by November 5, 2020 and position will remain opened until filled. 

  • A cover letter that includes a statement of research experience and interests,
  • A curriculum vitae,
  • PDF copies of a recent publication or writing sample,
  • Contact information of three professional references.


UMass Amherst is committed to a policy of equal opportunity without regard to race, color, religion, gender, gender identity or expression, age, sexual orientation, national origin, ancestry, disability, military status, or genetic information in employment, admission to and participation in academic programs, activities, and services, and the selection of vendors who provide services or products to the University.  To fulfill that policy, UMass Amherst is further committed to a program of affirmative action to eliminate or mitigate artificial barriers and to increase opportunities for the recruitment and advancement of qualified minorities, women, persons with disabilities, and covered veterans.  It is the policy of the UMass Amherst to comply with the applicable federal and state statutes, rules, and regulations concerning equal opportunity and affirmative action.

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