G/R27639P

Post-Doctoral Associate - Jackson Lab

CAES-Crop & Soil Sciences

Since our founding in 1785, the University of Georgia has operated as Georgia’s oldest, most comprehensive, and most diversified institution of higher education (https://www.uga.edu/). The proof is in our more than 235 years of academic and professional achievements and our continual commitment to higher education. UGA is currently ranked among the top 20 public universities in U.S. News & World Report. The University’s main campus is located in Athens, approximately 65 miles northeast of Atlanta, with extended campuses in Atlanta, Griffin, Gwinnett, and Tifton. UGA employs approximately 3,000 faculty and more than 7,700 full-time staff. The University’s enrollment exceeds 40,000 students including over 30,000 undergraduates and over 10,000 graduate and professional students. Academic programs reside in 18 schools and colleges, as well as a medical partnership with Augusta University housed on the UGA Health Sciences Campus in Athens.

Employee

M-F 8AM-5PM, hours may vary.

Commensurate with Experience

12/01/2024

10/30/2024

Yes

Athens Area

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Additionally, USG supports Freedom of Expression as stated in Board Policy 6.5 Freedom of Expression and Academic Freedom found online at https://www.usg.edu/policymanual/section6/C2653.

Develop biologically-consistent machine learning algorithms/solutions for plant/animal genomics (e.g. sequence level Large Language Models (LLMs) to omic level interactions with graph neural networks (GNNs) )

30

Leverage models to generate testable hypotheses on gene regulation’s role in improving known or developing novel plant traits. Doing so in zero-shot, one-shot, and multi-shot experimental campaigns.

30

Explore the use of Scientific AI Agents for exploring and optimizing plant traits through the compiling of out-of-domain open-source data, in-domain high-fidelity data, and access to query, and iterate over, new experiments.

30

Career development in a highly interactive and interdisciplinary environment

10

Post-Doctoral Associate AD

Exempt

1.00

Does solving challenging biological and computational questions with novel algorithms and genomic data that can transform agriculture excite you? Does working at the intersection of applied mathematics/engineering, genomics/epigenomics and plant biology interest you?

Join a team of researchers at the University of Georgia working to unravel how genomic sequences and epigenetic data affect gene regulation and plant development and build the next generation of “biologically-consistent” AI models that will reimagine the potential of plant systems. We are exploring new algorithmic approaches, including biologically-informed Machine Learning/AI (e.g. Large Language Models, Graph Neural Networks) and active learning, to derive biological insights into genome organization, structure and function as it relates to how genes are regulated, interact, and, ultimately, lead to new phenotypes.

As a Postdoctoral Associate, the primary foci will be to work with large genomic and phenotypic data sets to integrate across biological scales and derive new hypotheses about gene function that can be tested. You will work in close collaboration with Scott Jackson (UGA-Crop and Soils Sciences), Bob Schmitz (UGA-Genetics) and Ethan Pickering (UGA and Bayer Crop Science).

Ph.D. in engineering, computational biology, computer science, mathematics, statistics, or a related discipline, or Biology-related discipline with relevant experience.

• Knowledge of any of the following: data-driven model development, machine learning, deep learning, linear algebra, optimization, neural networks (LLMs, GNNs, etc.) or gaussian process regression, active learning, Bayesian experimental design, Bayesian optimization
• Knowledge in coding, e.g. Python, Matlab, and building open-sourced packages.
• A strong track record of research publications

Lifting 25 lbs, prolonged sitting at office desk.

Yes

No

No

No

No

No

Yes

Offers of employment are contingent upon completion of a background investigation including, a criminal background check demonstrating your eligibility for employment with the University of Georgia; confirmation of the credentials and employment history reflected in your application materials (including reference checks) as they relate to the job-based requirements of the position applied for; and, if applicable, a satisfactory credit check. You may also be subject to a pre-employment drug test for positions with high-risk responsibilities, if applicable. Please visit the UGA Background Check website.

For questions concerning this position or recruitment progression, please refer to the Recruitment Contact listed below.

Scott Jackson

sjackson@uga.edu