Requisition Id 6233
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 applying classical and ab initio molecular dynamics simulations and machine learning methods to understand interfacial behavior and chemical reactions of liquid absorbents used in separations.
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 better understanding and control of interfaces and mechanisms of the chemical reactions manifested in improved separations.
Computational methods will primarily involve ab initio, force field-based, constant pH, and machine-learning-based molecular dynamics simulations of interfacial transport, kinetics, and spectroscopic observables. You will also work within a multidisciplinary multi-institutional team involving specialists in theory, synthesis, nonlinear spectroscopy, and surface characterization.
- Work with a diverse team of scientists seeking to advance scientific understanding of how liquid absorbents organize at the interfacecan and how to control the interface to improve gas transport and reactivity
- Conduct molecular dynamics simulations and machine learning-based exploration of potential energy surfaces and chemical reactions in bulk and at the interface
- Independently plan and conduct simulations and work with experimentalists to help interpret spectroscopic results and guide the design of synthetic antiscalants
- 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
- 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 of predicting bulk and interfacial thermodynamic and transport properties
- Experience or knowledge in some of the following areas: (i) training of machine-learning-based atomistic potentials; (iI) classical and/or ab initio molecular dynamics simulations of liquids; (iii) advanced free energy simulation methods (e.g., constrained MD, Metadynamics, Umbrella sampling); (iv) density functional theory calculations; (v) reaction rate theory calculations; and (vi) modeling of non-linear spectroscopy
- 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
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 up to 24 months with the potential for extension. Initial appointments and extensions are subject to performance and availability of funding.
Three letters of reference are required and can be uploaded to your profile or emailed directly to PSDrecruit@ornl.gov. Please include the title of the position in the subject line.
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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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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.