Post-Doctoral Associate - Pickering Lab
Posting Details
Position Details
Posting Number G/R32483P Working Title Post-Doctoral Associate - Pickering Lab Department CAES-Crop & Soil Sciences About the University of Georgia
Chartered by the state of Georgia in 1785, the University of Georgia is the birthplace of public higher education in America and is the state’s flagship university (https://www.uga.edu/) . The proof is in our more than 240 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 3,100 faculty and more than 7,700 full-time staff. The University’s enrollment exceeds 41,000 students including over 31,000 undergraduates and over 10,000 graduate and professional students. Academic programs reside in 19 schools and colleges, including our newly established School of Medicine.
About the College/Unit/Department College/Unit/Department website Employment Type Employee Additional Schedule Information
Monday through Friday 8AM-5PM. Occasional travel for conferences.
Advertised Salary Commensurate with Experience Anticipated Start Date 06/01/2026 Posting Date 03/19/2026 Closing Date Open Until Filled Yes Special Instructions to Applicants Location of Vacancy Athens Area EOO Statement
The University of Georgia is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to age, color, disability, genetic information, national origin, race, religion, sex, or veteran status or other protected status. Persons needing accommodations or assistance with the accessibility of materials related to this search are encouraged to contact Central HR ( hrweb@uga.edu ).
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Duties/Responsibilities
Duties/Responsibilities
Develop Agentic AI systems for agricultural design & prediction
• Architect agent workflows (data/literature ingestion → modeling → evaluation → iteration) for genomics and crop modeling.
• Foundation-model or representation-learning approaches for genotype/sequence/omics; uncertainty-aware prediction; decision support for selection.
• Hybrid mechanistic + learned models; neural ODEs / constrained learning; spatiotemporal modeling across G×E×M.
Percentage of time 70 Duties/Responsibilities
Create benchmarks, datasets, and evaluation protocols
• Reproducible benchmarks across crops, environments, and tasks; rigorous ablations; robustness + generalization testing.
Percentage of time 15 Duties/Responsibilities
Career development & scholarly dissemination
• Papers, talks, open-source releases, mentoring students, and participating in interdisciplinary collaborations.
Percentage of time 15
Position Details
Position Information
Classification Title Post-Doctoral Associate AD FLSA Exempt UGA Job Code FTE 1.00 Minimum Qualifications Position Summary
Agentic AI Is Rapidly Changing Nearly Every Domain, From Academia To Industry. Agriculture Is No Different. These Postdoctoral Opportunity Will Look To Research And Build Agentic Scientific AI Systems That Can Design, Predict, And Optimize Agricultural Outcomes—across Crops, Environments, And Management Regimes. We Are Seeking a Postdoctoral Associate To Develop The Next Generation Of Agentic AI For Agricultural Design And Prediction, Spanning
• Genomics agents that assemble AI-native genomic prediction and selection models (e.g., DNA foundation-models, GNN/sequence architectures for breeding decisions, pangenomic models).
• Crop Growth Model agents that create AI-native crop growth models—including Bio-Informed Neural Networks (BINNs) and hybrid dynamical systems that fuse mechanistic constraints with large-scale data.
• Scientific agent workflows that can ingest literature + datasets, propose modeling choices, run experiments, quantify uncertainty, and iteratively improve models with human-in-the-loop evaluation.
This role sits at the intersection of applied mathematics, machine learning, genomics, crop science, and dynamical systems, and will be carried out in a highly interdisciplinary team environment.
Potential Focus Areas
• Agentic Genomics for Prediction & Selection: Build agents that can automatically construct, evaluate, and adapt genomic/pangenomic/editing prediction pipelines (from raw genotypes/omics to breeding-value predictions), including modern representation learning and uncertainty-aware decision support.
• Agentic AI Crop Growth Models (AI-CGMs): Develop hybrid modeling agents that learn AI-native CGMs (e.g., BINNs; constrained neural ODEs; spatiotemporal models) integrating genomics, phenomics, physiology, weather, soils, remote sensing, and management data.
What Success Looks Like (12–24 Months)
• A working agentic modeling stack demonstrated on at least one “end-to-end” crop use case (e.g., data → genomics predictions + AI-CGM → intervention suggestions with uncertainty).
• Publications in top venues (ML for science, computational biology, agronomy/crop modeling) and public releases of code/benchmarks.
• Clear pathways to stakeholder deployment (breeders, agronomists, extension, or industry R&D).
Relevant/Preferred Education, Experience, Licensure, Certification in Position
Mathematical + computational depth, especially one or more of:
• Dynamical systems, scientific computing, numerical methods, optimization
• Probabilistic modeling / Bayesian methods / uncertainty quantification
• Representation learning for sequences/graphs; geometric deep learning
Proficiency (or Strong Interest) In Any Of
• Genomics, quantitative genetics, genomic prediction, GWAS, multi-omics integration
• Crop growth modeling, ecophysiology, spatiotemporal modeling, remote sensing + agronomy
• Agentic AI / tool-using LLM systems / workflow orchestration for science
Knowledge, Skills, Abilities and/or Competencies
Candidates Should Have Strength In Several Of The Following
• Machine learning / deep learning; LLMs, GNNs, sequence models; hybrid modeling
• Linear algebra, optimization, probabilistic modeling, experimental design, active learning
• Scientific programming in Python (other languages a bonus); building maintainable, open-source codebases and reproducible pipelines (containers, workflows, benchmarking)
• Ability to collaborate across disciplines and communicate clearly with both technical and domain audiences
Physical Demands
Lifting 25 lbs, prolonged sitting at office desk.
Is this a Position of Trust? Yes Does this position have operation, access, or control of financial resources? No Does this position require a P-Card? No Is having a P-Card an essential function of this position? No Is driving a requirement of this position? No Does this position have direct interaction or care of children under the age of 18 or direct patient care? No Does this position have Security Access (e.g., public safety, IT security, personnel records, patient records, or access to chemicals and medications) Yes Background Investigation Policy
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 .
Contact Information
Recruitment Contact
Contact Details
For questions concerning this position or recruitment progression, please refer to the Recruitment Contact listed below.
Recruitment Contact Name Ethan Pickering Recruitment Contact Email Ethan.Pickering@uga.edu Recruitment Contact Phone
Posting Specific Questions
Required fields are indicated with an asterisk (*).
Applicant Documents
Required Documents
• Resume/CV
• Sample Publications
Optional Documents
• Cover Letter
• List of References with Contact Information
• Other Documents #1
Higher Education
Research, Analyst, and Information Technology
Full-time