Postdoctoral Research Associate - AI Genomic Photosynthesis

Select how often (in days) to receive an alert:

Oak Ridge National Laboratory (ORNL) is seeking an ambitious postdoctoral scientist with keen interest in artificial intelligence (AI) / machine learning (ML) and photosynthesis to join the new pilot study of Generative Pretrained Transformer for genomic photosynthesis (GPTgp). The GPTgp project aims to develop a foundational holistic model of photosynthesis that will scale from plant genomics to phenomics with biological mechanisms embedded in deep neutral networks.

GPTgp will allow task-specific training and transfer learning across reactions, pathways, biodesigns, and species. It can be fine-tuned for downstream applications such as predicting genetic perturbations, optimizing photosynthetic apparatus for performance, selecting top performing genotypes for various environmental conditions, and predicting photosynthesis at multiple scales. The selected postdoctoral scientist will work with a team of mathematicians, computational scientists, plant geneticists and physiologists, and data scientists to tackle fundamental issues in AI/ML-based photosynthesis research and applications.

The selected scientist will have access to the world’s most advanced resources in computing (https://(Use the "Apply for this Job" box below). ) and plant phenotyping (https:// ).

GPTgp is a pilot project initiated in September 2025 with funding from the US Department of Energy and will initially last for two years. It is expected that the success of this pilot project will pave the way for future, much broader and deeper AI/ML-based research and applicational efforts in genomic photosynthesis.

Major Duties/Responsibilities:

• Compile and organize diverse multiscale datasets from plant genomics to phenomics.
• Develop and test different tokenization and embedding strategies for multimodal plant datasets for training a foundational model of genomic photosynthesis.
• Develop functionality requirements for a data lakehouse for AI genomic photosynthesis research and applications.
• Assist in the development of AI architecture for holistic genomic photosynthesis modeling.
• Evaluate performances of AI genomic photosynthesis models.
• Report advances to program management and broader scientific communities.
• Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service. Promote equal opportunity by fostering a respectful workplace – in how we treat one another, work together, and measure success.

Basic Qualifications:

• A PhD in evolutionary biology, plant biology, genomics, bioinformatics, mathematics, statistics, computer / computational science or related field completed within the last five years.
• Experience in AI/ML.
• Skills in a programing language are commonly used in AI/ML.

Preferred Qualifications:

• Experience in DNA and protein AI/ML models and multimodal datasets.
• Knowledge in different deep learning architectures, tokenization and embedding methods.
• Experience in dimensional reduction methods and visualization tools.
• Effective writing and communication skills as demonstrated in publication and presentation.
• Demonstrated ability to work both independently and collaboratively as part of a multidisciplinary team.

Special Requirements:

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 12 months with the potential for an extension of up to 24 months. Initial appointments and extensions are subject to performance and the availability of funding.

Please upload the following materials directly to your application: a one-page research statement, a list of no more than three most important publications (dissertation is considered, please attach a copy if not available online), and a list of three referees.

Instructions to upload documents to your candidate profile:

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

For more information, please…