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Urgent! Postdoctoral Research Associate - AI for Genomic Photosynthesis Job Opening In Oak Ridge – Now Hiring Oak Ridge National Laboratory

Postdoctoral Research Associate AI for Genomic Photosynthesis



Job description

Requisition Id 15358 

Overview:

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 () and plant phenotyping ().

 

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:

  • Deep experience in developing large language models.
  • 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 contact Lianhong-gu@ornl.gov.


Security, Credentialing, and Eligibility Requirements:
For employment at Oak Ridge National Laboratory (ORNL), a Real ID compliant form of identification will be required.

Additionally, ORNL is subject to Department of Energy (DOE) access restrictions.

All employees must also be able to obtain and maintain a federal Personal Identity Verification (PIV) card as mandated by Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, which requires a favorable post-employment background investigation.


To obtain this credential, new employees must successfully complete and pass a Federal Tier 1 background check investigation.

This investigation includes a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last year.

This includes marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws.


For foreign national candidates:
If you have not resided in the U.S. for three consecutive years, you are not eligible for the PIV credential and instead will need to obtain a favorable Local Site Specific Only (LSSO) risk determination to maintain employment.

Once you meet the three-year residency requirement, you will be required to obtain a PIV credential to maintain employment.

 
 

 

 

About ORNL:

As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an impressive 80-year legacy of addressing the nation’s most pressing challenges.

Our team is made up of over 7,000 dedicated and innovative individuals! Our goal is to create an environment where a variety of perspectives and backgrounds are valued, ensuring ORNL is known as a top choice for employment.

These principles are essential for supporting our broader mission to drive scientific breakthroughs and translate them into solutions for energy, environmental, and security challenges facing the nation.

 

ORNL offers competitive pay and benefits programs to attract and retain individuals who demonstrate exceptional work behaviors.

The laboratory provides a range of employee benefits, including medical and retirement plans and flexible work hours, to support the well-being of you and your family.

Employee amenities such as on-site fitness, banking, and cafeteria facilities are also available for added convenience.

 

Other benefits include the following: Prescription Drug Plan, Dental Plan, Vision Plan, 401(k) Retirement Plan, Contributory Pension Plan, Life Insurance, Disability Benefits, Generous Vacation and Holidays, Parental Leave, Legal Insurance with Identity Theft Protection, Employee Assistance Plan, Flexible Spending Accounts, Health Savings Accounts, Wellness Programs, Educational Assistance, Relocation Assistance, and Employee Discounts.

 

If you have difficulty using the online application system or need an accommodation to apply due to a disability, please email: ORNLRecruiting@ornl.gov.

 

#LI-DC1

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.


If you have trouble applying for a position, please email ORNLRecruiting@ornl.gov.


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.


Required Skill Profession

Life Scientists



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