Post-Doctoral Associate - Pickering Lab
About the role
The Post-Doctoral Associate will develop agentic AI systems for agricultural design and prediction, focusing on genomics and crop modeling. The role involves developing agent workflows, creating benchmarks, and career development.
Responsibilities
Develop agentic AI systems for agricultural design and prediction, including genomics and crop modeling.
Create benchmarks, datasets, and evaluation protocols, ensuring reproducibility and robustness.
Career development and scholarly dissemination through papers, talks, open-source releases, mentoring students, and interdisciplinary collaborations.
Requirements
Mathematical and computational depth, particularly in dynamical systems, scientific computing, numerical methods, and optimization.
Experience with probabilistic modeling, Bayesian methods, and uncertainty quantification.
Proficiency or strong interest in genomics, quantitative genetics, genomic prediction, GWAS, multi-omics integration, crop growth modeling, ecophysiology, spatiotemporal modeling, remote sensing, and agronomy.
Knowledge of agentic AI, tool-using LLM systems, and workflow orchestration for science.
Strong programming skills in Python and ability to build maintainable, open-source codebases and reproducible pipelines.
Qualifications
Ph.D. in relevant field (e.g., computational biology, agronomy, computer science).
Experience in agentic AI, genomics, crop modeling, and interdisciplinary research.
Excellent communication and collaboration skills.
Skills
Machine learning and deep learning.
LLMs, GNNs, sequence models.
Hybrid modeling.
Linear algebra, optimization, probabilistic modeling, experimental design, and active learning.
Scientific programming in Python.
Benefits
Commensurate with experience.
Pay
Commensurate with experience.
Schedule
Monday through Friday, 8AM-5PM. Occasional travel for conferences.