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Targeted Postdoctoral Fellowships at NIMBioS

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Since 2009, NIMBioS has provided opportunities for postdoctoral scholarship at the interface between mathematics and the biological sciences. Targeted Postdoctoral Fellowships provide support for specific research questions on projects directed by UT faculty.

Targeted Postdoctoral Fellows will join the NIMBioS Fellow community. The NIMBioS community provides opportunities for collaboration with other Fellows, faculty, and numerous visiting researchers, career mentoring, career development workshops, grant-writing, outreach and education, and partner/spousal accommodation.

NIMBioS is committed to promoting diversity in all its activities. Diversity is considered in all its aspects, social and scientific, including gender, ethnicity, scientific field, career stage, geography and type of home institution. Questions regarding diversity issues should be directed to You can read more about our Diversity Plan on our NIMBioS Policies web page. The NIMBioS building is fully handicapped accessible.

For questions about Targeted Fellowships, contact the specific faculty member associated with the current opportunities below.

Current Targeted Postdoctoral Fellowships

Postdoctoral Research Associate

A post-doctoral research associate position is available in the Spatial Analysis Lab at NIMBioS. The project will focus on characterizing forest structure and biomass from National Agriculture Imagery Program (NAIP) digital surface model (DSM) data acquired in 2018 for Tennessee and Virginia. The post-doctoral associate will be expected to develop plot-level accuracy assessments, state-wide evaluations of post-stratified forest volume and biomass estimates, and R code or specialized methodologies to process and/or analyze the various spatial data sets. Click here to apply.

Targeted Postdoctoral Fellowship in Mathematical Modeling of Biological Systems

Applications are currently being accepted for a postdoctoral position in mathematical modeling of biological systems at NIMBioS and in the Fefferman Lab at the University of Tennessee at Knoxville. This is a full-time, one year position, with the potential for renewal.

The work involves mathematical modeling, focusing initially on analysis and simulations of difference and differential equation models of physiological processes. An ideal candidate would have some experience in at least one relevant area of applied bio-mathematical research. Beyond the initial project, this position will entail collaborating to design new mathematical models for a diversity of novel applications. Any candidate should be comfortable with a variety of modeling techniques and willing to learn new areas of modeling application in collaboration with interdisciplinary research teams. The researcher will be expected to help formulate mathematical models, characterize analytic properties of the systems, implement numerical simulations, take a primary role in preparing manuscripts for publication, contribute to a collaborative research group environment, and participate in preparation of new grant proposals.


  • Ph.D. in some pertinent field. Such fields could include, but are not limited to applied mathematics, epidemiology, ecology, evolutionary biology, physics, engineering, or computer science
  • Research experience in applied mathematical modeling (epidemiology or evolutionary biology are preferred, but not required)
  • Familiarity with at least two of the following mathematical modeling techniques: ODEs, PDEs, SDEs, Game Theory, Cellular Automata, Network Theory, Decision Theory, and Agent Based Modeling
  • Ability to write clearly and scientifically (e.g. to produce drafts of papers for publication in scientific journals and web-based public outreach without too much oversight); evidence of successful prior publication is a plus
  • Ability to work/communicate with a multidisciplinary team
  • Fluency in a mathematical programming environment (preferably Matlab, but Mathematica, R, Python, or equivalent are also acceptable)

The Fefferman Lab is affiliated with the Department of Ecology & Evolutionary Biology, the Department of Mathematics, and the National Institute for Mathematical and Biological Synthesis (NIMBioS) at the UT-Knoxville. The candidate will be welcome to participate in any/all of these communities.

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Review of applications will continue until the position is filled.

How to apply: you must complete an application on our online registration system:

  1. Click here to access the system
  2. Login or register
  3. Complete your user profile (if you haven't already)
  4. Find "Postdoctoral Fellowship: Mathematical Modeling of Biological Systems" under Current Events Open for Application and click on Apply

You will be asked to upload a single PDF document, organized as follows:

  • Cover letter (1-2 pages)
  • Names and contact information for three references
  • Full CV

For more information, contact Nina H. Fefferman at

All qualified applicants will receive equal consideration for employment and admissions without regard to race, color, national origin, religion, sex, pregnancy, marital status, sexual orientation, gender identity, age, physical or mental disability, or covered veteran status.

Eligibility and other terms and conditions of employment benefits at The University of Tennessee are governed by laws and regulations of the State of Tennessee, and this non-discrimination statement is intended to be consistent with those laws and regulations.

In accordance with the requirements of Title VI of the Civil Rights Act of 1964, Title IX of the Education Amendments of 1972, Section 504 of the Rehabilitation Act of 1973, and the Americans with Disabilities Act of 1990, The University of Tennessee affirmatively states that it does not discriminate on the basis of race, sex, or disability in its education programs and activities, and this policy extends to employment by the University.

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NIMBioS is supported by the National Science Foundation through NSF Award #DBI-1300426, with additional support from The University of Tennessee, Knoxville. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
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