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Oak Ridge National Laboratory is the largest US Department of Energy science and energy laboratory, conducting basic and applied research to deliver transformative solutions to compelling problems in energy and security.


We are seeking a Postdoctoral Research Associate who will support the Computational and Predictive Biology Group in the Biosciences Division (BSD), Biological and Environmental Systems Science Directorate (BESS) at Oak Ridge National Laboratory (ORNL) with experience in computational biology and microbial ecology to take on an important role developing computational tools for designing synthetic communities of plant-associated microbes and investigating model community formation and functional dynamics.


The candidate will work with a diverse and talented team of biologists, computer scientists, and developers in a joint effort between the Plant Microbe Interfaces (PMI and DOE Systems Biology Knowledgebase (KBase projects, and will have many opportunities to broaden their knowledge, develop collaborative networks and their own research. This position provides the opportunity to conduct cutting-edge research with access to suitable high-performance computing resources and ORNL’s Leadership Class Supercomputer (


The Biosciences Division (BSD) at Oak Ridge National Laboratory (ORNL) is focused on advancing science and technology to better understand complex biological systems and their relationship with the environment. BSD has expertise and special facilities in genomics, computational systems biology, microbiology, microbial ecology, biophysics and structural biology, and plant sciences. Research in the Computational and Predictive Biology group includes methods development and use to investigate, analyze and model observed phenomena more holistically and precisely, and to improve the predictive capabilities of the computational models toward guided discovery and experimental design.


Major Duties/Responsibilities: 

In this role, you will work collaboratively with PMI and KBase researchers to:

  • Develop software to model compositional and functional shifts of microbial communities
  • Develop software to help with design of synthetic microbial communities for improved plant phenotypes.
  • Organize relevant PMI experimental datasets on isolates and synthetic communities
  • Develop, package, and apply computational methods in the KBase platform, which will be shared and disseminated across the microbiome research community
  • Present research progress in project meetings and national/international conferences
  • Contribute to ongoing projects in the group, and successfully define and develop your own projects
  • Publish original work and scientific results in peer-reviewed journals


Basic Qualifications:

  • A PhD in Computational Biology, Bioinformatics, Computer Science, Data Science, Chemical Engineering, Bioengineering, Biology or a related field completed within the last 5 years
  • Strong computational science expertise and a solid background in scientific programming, data science, computational techniques and/or computational biology
  • Programming experience using Python
  • Familiar with data analysis and understanding of data models to represent biological concepts
  • Experience in analyzing microbiome datasets


Preferred Qualifications:

  • Background in any of the following areas: modeling synthetic microbial community, modeling plant-microbe or plant-pathogen interactions, microbiology, ecological and evolutionary genomics
  • Experience with modeling tools to study metabolic mechanisms of interaction within a microbial community
  • Strong track record in developing software tools
  • Demonstrated strength and efficiency in technical writing
  • Strong experience with software engineering best practices
  • Excellent written and oral communication skills
  • Motivated self-starter with the ability to work independently and to participate creatively in collaborative teams across the laboratory 
  • Ability to function well in a fast-paced research environment, set priorities to accomplish multiple tasks within deadlines, and adapt to ever changing needs


Please submit three letters of reference when applying to this position. You can upload these directly to your application or have them sent to with the position title and number referenced in the subject line.


Instructions to upload documents to your candidate profile:

  • Login to your account via
  • View Profile
  • Under the My Documents section, select Add a Document


Applicants cannot have received their Ph.D. more than five years prior to the date of application and must complete all degree requirements before starting their appointment. The appointment length will be for up to 24 months with the potential for extension. Initial appointments and extensions are subject to performance and the availability of funding.


Moving can be overwhelming and expensive. UT-Battelle offers a generous relocation package to ease the transition process. Domestic and international relocation assistance is available for certain positions. If invited to interview, be sure to ask your Recruiter (Talent Acquisition Partner) for details.

For more information about our benefits, working here, and living here, visit the “About” tab at


This position will remain open for a minimum of 5 days after which it will close when a qualified candidate is identified and/or hired.

We accept Word (.doc, .docx), Adobe (unsecured .pdf), Rich Text Format (.rtf), and HTML (.htm, .html) up to 5MB in size. Resumes from third party vendors will not be accepted; these resumes will be deleted and the candidates submitted will not be considered for employment.

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ORNL is an equal opportunity employer. All qualified applicants, including individuals with disabilities and protected veterans, are encouraged to apply. UT-Battelle is an E-Verify employer.