Job Description

Post-Doctoral Research Associate - Computational Materials Science and Machine Learning


This position involves computational research on nuclear materials, with an emphasis on f-elements (lanthanides and actinides), molten salts, interfacial science, and energy-related processes within a multi-scale modeling framework. The main task focuses on developing and using machine learning interatomic potentials, advanced free energy simulations, and high-performance computing to predict chemical and materials properties, such as thermochemical behaviors and interfacial interactions relevant to nuclear applications. Duties include technical interactions with undergraduate and graduate students, contributing to and developing new research initiatives, writing peer-reviewed scientific journal articles, and technical management of research projects. The appointment would be a limited term appointment, approximately 1 year with the possibility of renewal for future years. The end goal after the appointment would be for you to secure a permanent position that is compatible with your interest.



Development and evaluation of statistical and machine learning tools for designing and understanding functional materials using the leadership class high performance computing facilities. Work with multi-disciplinary teams to apply modeling and simulation techniques to bulk materials and interfaces, supporting both fundamental research and applied programs. Publishing papers in high-quality refereed journals. Actively collaborating with industry, academia, government labs, and applications developers in a variety of venues.

Required Qualifications:

Ph.D. degree in Materials Science, Chemical Engineering, Computational Chemistry, or an equivalent field. A well-established track record of research in materials science/computational modeling/chemistry. Experience in employing advanced statistical mechanics methods and machine learning for simulations of materials.

Preferred Qualifications:

Programming experience using Python for workflow development, scientific computing, and data analysis and visualization. Demonstrated knowledge and experience in advanced free energy simulations methods, such as thermodynamic integration, metadynamics, and umbrella sampling. Experience in developing and utilization of machine learning interatomic potentials to enhance predictive modeling of chemical processes and materials. Demonstrated experience in modeling solid-liquid interfaces. Excellent interpersonal skills, oral and written 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.

Work Location:

Location: Knoxville, TN Onsite

Compensation and Benefits:

Anticipated hiring range: $70,000 - $75,000

Application Instructions:

Interested candidates should submit a letter of application, curriculum vitae, and names and addresses of three references. For questions or inquiries please contact Prof. Ivanov, email:

aivanov@utk.edu

. Review of applications will begin immediately and will continue until the position is filled.

About The Department:

The Department of Nuclear Engineering at the University of Tennessee, Knoxville, established in 1957, was the first of its kind and is considered one of the most prestigious in the United States. Its mission is supported by internationally recognized faculty and advanced research programs, enhanced by close ties with institutions such as Oak Ridge National Laboratory, the Y-12 Nuclear Security Complex, UCOR, and the East Tennessee Technology Park, as well as over one hundred nuclear-related companies within fifty miles of Knoxville. The department offers programs, with its graduate program consistently ranked among the top in the nation by U.S. News and World Report.



The University of Tennessee, Knoxville, has shaped leaders, changemakers, and innovative thinkers since its founding in 1794. The university is home to more than 38,000 students and 10,000 statewide employees--the Volunteers--who uphold the university's tradition of lighting the way for others through leadership and service.



UT Knoxville offers over 900 programs of study across 14 degree-granting colleges and schools. As Tennessee's flagship land-grant university, its footprint spans the entire state. The university holds the highest Carnegie classification for research activity and has deep partnerships with industry leaders and the US Department of Energy's largest multidisciplinary laboratory, Oak Ridge National Laboratory.



The Knoxville campus serves and recruits for UT Knoxville, including the Institute of Agriculture and the Space Institute, as well as the UT Institute of Public Service.



UT Knoxville considers its employees its number one asset. With values that focus on work-life balance, compensation, and innovation leadership, all Vols are supported to advance professionally. Employees have access to career development and coaching, continued education, and an extensive list of development and training possibilities. The Volunteer employee experience implements structures and practices to attract and retain top-tier talent, fostering a strong staff community and supporting a culture of involvement and engagement for everyone.



The university holds a strong commitment to its land-grant mission of learning and engagement, with a tradition of service and leadership that carries that Volunteer spirit throughout the state and around the world. It has been ranked nationally as "Best Employer for New Graduates," "One of America's Best Large Employers," and "Best Workplace for Women," and has been designated as "Best Place for Working Parents" by Forbes Magazine.



Apply today and join the Tennessee Volunteer community!