Requisition Id 8587
Oak Ridge National Laboratory is the largest US Department of Energy science and energy laboratory, conducting basic and applied research to deliver transformative solutions to compelling problems in energy and security.
We are seeking a Postdoctoral Research Associate who will focus on ab initio and classical molecular dynamics simulations and machine learning methods to understand the chemistry of molten salts and design molten salts compositions for energy related applications. This position resides in the Chemical Separations Group of the Chemical Sciences Division, Physical Sciences Directorate (PSD) at Oak Ridge National Laboratory (ORNL). In this role, you will perform computational studies aimed at understanding of thermodynamic and kinetic principles of ion pairing and coordination that govern the chemistry of molten salts at the forefront of the field through high-performance computing (HPC) and data science. Computational methods will primarily involve ab initio, force field-based, and machine-learning-based molecular dynamics simulations of molten salts. You will also work within a multidisciplinary multi-institutional team involving specialists in first principles calculations, data science, spectroscopy, and experimental characterization.
- Work with a diverse team of scientists seeking to advance scientific understanding of the chemical properties of molten salts and use this knowledge to design molten salts compositions for specific energy related applications
- Develop and/or employ methods for machine learning-based exploration of potential energy surfaces and chemical reaction networks
- Conduct molecular dynamics simulations and/or free energy perturbation and other methods for predicting thermodynamic and kinetic properties, chemical reaction mechanisms, and spectroscopic observables
- Participate in project planning and execution
- Present and report research results and publish scientific results in peer-reviewed journals in a timely manner
- Ensure compliance with environment, safety, health, and quality program requirements
- Maintain strong dedication to the implementation and perpetuation of values and ethics
- A Ph. D. in theoretical or computational chemistry or closely related field in physical chemistry or chemical physics completed within the last five years
- Experience with molecular dynamics simulations and/or free energy perturbation and other methods for predicting thermodynamic, kinetic, and transport properties from molecular simulations
- Experience or knowledge in some of the following areas: (i) training of machine-learning-based potentials; (ii) method development for machine learning-based exploration of potential energy surfaces; (iii) classical and/or ab initio molecular dynamics simulations of liquids, including application of the enhanced sampling methods; (iv) density functional theory calculations; (v) development and evaluation of scalable computer codes for leadership class high performance computing facilities available at ORNL and other DOE leadership computing facilities.
- Excellent record of productive and creative research as demonstrated by publications in peer-reviewed journals
- 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
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@example.com with the position title and number referenced in the subject line.
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- Under the My Documents section, select Add a Document
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.
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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.
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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.