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Postdoctoral Research Associate
3 months ago
Requisition Id 13218
Overview:
Oak Ridge National Laboratory (ORNL) is the largest US Department of Energy science and energy laboratory, conducting basic and applied research to deliver solutions to compelling problems in energy and security. Our capabilities span a broad range of scientific and engineering disciplines, enabling the Laboratory to explore fundamental science challenges and to carry out the research needed to accelerate the delivery of solutions to the marketplace.
Key Research Areas:
ORNL has world-class computational facilities to utilize in this project, from daily access to an NVIDIA DGX A100 system for prototyping neural networks, to the latest NVIDIA H100 architectures for limited projects, and the potential to scale algorithms (e.g., foundation models) on the fastest high-performance computing (HPC) system for open science in the world, Frontier. The candidate will join a team of computer vision, machine learning, and data science experts to accomplish project goals. The candidate will learn state-of-the-art deep learning methods and the associated biological domain knowledge to ensure the accuracy and validity of model results. Importantly, this team has a track record of real-world impact with tools in use around the world and significant contributions to biological knowledge through use of computing and phenomics.
Major duties/responsibilities include:
Lead research and development of deep learning models for segmentation, classification, object detection, etc., applied to multimodal time series image data Contribute to the development of multimodal foundation models for plant science using data from APPL and additional internal and external data sources Present research progress in project meetings and national/international conferences Publish scientific results in peer-reviewed journals in a timely manner Maintain detailed and accurate records Acquire and analyze data in keeping with project scheduling Ensure compliance with environmental, safety, health and quality program requirements Maintain strong dedication to the implementation and perpetuation of values and ethicsBasic Qualifications:
A Ph.D. in computer science, applied mathematics, plant biology, or related fields. Applicants cannot have received the most recent degree more than five years prior to the date of application and must complete all degree requirements before starting their appointment.Preferred Qualifications:
Experience in image-based plant phenotyping using structured (e.g., RGB, thermal, hyperspectral) and unstructured (e.g., point cloud) data Experience with implementing, training, and using deep neural networks with frameworks like PyTorch and languages like Python (preferred) Experience in image analysis with traditional computer vision tools (e.g., OpenCV, PlantCV) Experience with linking key traits with underlying genes using analyses like GWAS or molecular biology skills Effective writing and communication skills with a strong publication record Desire to work both independently and collaboratively as part of a multidisciplinary teamInstructions 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 DocumentApplicants 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 24 months with the potential for extension. Initial appointments and extensions are subject to performance and the availability of funding.
Moving can be overwhelming and expensive. UT-Battelle offers a generous relocation package to ease the transition process. Domestic and international relocation assistance is available for certain positions. If invited to interview, be sure to ask your Recruiter (Talent Acquisition Partner) for details.
For more information about our benefits, working here, and living here, visit the “About” tab at jobs.ornl.gov.
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.
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.
