Postdoctoral Research Associate - Polymer Data Mining

Requisition Id 12244 

Overview: 

As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an extraordinary 80-year history of solving the nation’s biggest problems. We have a dedicated and creative staff of over 6,000 people! Our vision for diversity, equity, inclusion, and accessibility (DEIA) is to cultivate an environment and practices that foster diversity in ideas and in the people across the organization, as well as to ensure ORNL is recognized as a workplace of choice. These elements are critical for enabling the execution of ORNL’s broader mission to accelerate scientific discoveries and their translation into energy, environment, and security solutions for the nation.

We are seeking a Postdoctoral Research Associate who will support the Carbon and Composites Group in the Chemical Sciences Division, Physical Sciences Directorate at Oak Ridge National Laboratory (ORNL).  

Major Duties/Responsibilities:

• Utilize artificial neural networks (ANNs) for predicting electronic structure properties of conjugated polymers in different resolution.
• Design materials inversely based on desired physical properties by employing ANNs for the optimization process.
• Develop and implement generative models, including Variational Autoencoders (VAEs) and Generative Adversarial Networks (GANs)
• Design and train language models tailored for polymer molecules
• Understand the intricate relationship between polymer structure and properties, with an emphasis on utilizing generative models for property tailoring
• Develop, optimize, and troubleshoot code for large-scale molecular simulations and generative model training
• Implement cutting-edge machine learning techniques for the analysis of molecular data
• Publish papers in key journals and protect intellectual properties
• Ensure compliance with data management and data quality requirements
• Maintain strong commitment to the implementation and perpetuation of values and ethics
• Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service. Promote diversity, equity, inclusion, and accessibility by fostering a respectful workplace – in how we treat one another, work together, and measure success.

Basic Qualifications:

• A PhD in Computer Science, Computational Chemistry, Materials Science, or a related field completed within the last 5 years

Preferred Qualifications:

• Robust understanding of the theoretical foundations and practical applications of generative models in the context of polymer molecular structures.
• Experienced in cutting-edge language models and their adaptation to molecular data.
• Basic understanding of polymer chemistry, molecular dynamics, and materials science
• Expertise in programming languages commonly used in scientific computing, such as Python, TensorFlow, PyTorch, or equivalent.
• Experience in preprocessing and curating molecular data to facilitate effective model training.
• Strong background in machine learning, deep learning, and neural network architectures
• Strong analytical and problem-solving skills, particularly in addressing challenges related to generative model development and polymer science
• Excellent written and oral communication skills
• Motivated self-starter with the ability to work independently and to participate creatively in collaborative teams across the laboratory 
• Ability to function well in a fast-paced research environment, set priorities to accomplish multiple tasks within deadlines, and adapt to ever changing needs

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

Please submit three letters of reference when applying to this position. You can upload these directly to your application or have them sent to [email protected] with the position title and number referenced in the subject line.

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

Benefits at ORNL:  

ORNL offers competitive pay and benefits programs to attract and retain talented people. The laboratory offers many employee benefits, including medical and retirement plans and flexible work hours, to help you and your family live happy and healthy. Employee amenities such as on-site fitness, banking, and cafeteria facilities are also provided for convenience.

Other benefits include: Prescription Drug Plan, Dental Plan, Vision Plan, 401(k) Retirement Plan, Life Insurance, Pet Insurance, 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: [email protected] .

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 [email protected].

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.