Assistant Research Scientist

Job Title

Assistant Research Scientist

Agency

Texas A&M University

Department

Institute For Scientific Computation

Proposed Minimum Salary

Commensurate

Job Location

College Station, Texas

Job Type

Staff

Job Description

Our Commitment    

Texas A&M University is committed to enriching the learning and working environment by promoting a culture that respects all perspectives, talents & lived experiences.  Embracing varying opinions and perspectives strengthens our core values which are: Respect, Excellence, Leadership, Loyalty, Integrity, and Selfless Service. 

Who We Are

The Institute for Scientific Computation (ISC) is devoted to the design, analysis, and implementation of innovative computational tools to advance scientific and engineering research and education. ISC conducts multidisciplinary research under four disciplines of scientific computation: data management, mathematical modeling, numerical solutions, and visualization. Research includes advanced computational methods and numerical analysis; validation of numerical results; Field Programmable Gate Array (FPGA); advanced integrated data center; software architecture design; and visualization of multi-dimensional computational results.  

What We Want

The Assistant Research Scientist will focus on demonstrating the value of model-order reduction in creating simulation engines for digital twins applied to advanced nuclear energy systems that utilize molten salts. Our goal is to enable licensable innovations in advanced nuclear reactors through using leadership-class computing facilities and integration with the Computational and Data Science Group of the Department of Nuclear Engineering at Texas A&M University and with experiments carried at the molten salt research reactor facility. If the description sounds exciting to you, we invite you to apply to be considered for this opportunity to join our team.

What You Need to Know

Salary: Compensation will be commensurate based on the selected candidate’s education and experience.

Required Education and Experience:

• Ph.D. in Engineering, Applied Mathematics, or related field

Preferred Education and Experience:

• Ability to cultivate and maintain professional working relationships

• Good communication skills and leadership potential

• Demonstrated excellence in research related to time-dependent and parametric model-order reduction techniques (projection-based and/or non-intrusive), Bayesian inference, physics-guided machine learning, and digital twinning

• Experience with high-performance computing applications using Python and C++

Responsibilities:

• Research: Leads a reduced-order modeling effort for the development of a digital twin for a molten salt reactor; this research thrust will produce a real-time, multiphysics, surrogate model that is informed from full-order, high-resolution, simulations using the open-source OpenFOAM software. This research is expected to be published in tier-1 journals dealing with computational physics, data science, and applied mathematical modeling.

• Mentor: Co-mentors graduate students.

• Grant Proposals: Assists with the ideation and writing of grant proposals.

Why Texas A&M University? 

We are a prestigious university with strong traditions, Core Values, and a community of caring and collaboration.  Amenities associated with a major university, such as sporting and cultural events, state-of-the-art recreation facilities, the Bush Library and Museum, and much more await you.  Experience all that a big city has to offer but with a reasonable cost-of-living and no long commutes. 

• Health , dental , vision , life and long-term disability insurance with Texas A&M contributing to employee health and basic life premiums

• 12-15 days of annual paid holidays 

• Up to eight hours of paid sick leave  and at least eight hours of paid vacation each month

• Automatically enrollment in the Teacher Retirement System of Texas 

• Health and Wellness: Free exercise programs and release time

• Professional Development: All employees have access to free LinkedIn Learning  training, webinars, and limited financial support to attend conferences, workshops, and more 

• Employee Tuition Assistance and Educational Release time   for completing a degree while a Texas A&M employee

Instructions to Applicants: Applications received by Texas A&M University must either have all job application data entered or a resume attached. Failure to provide all job application data or a complete resume could result in an invalid submission and a rejected application. We encourage all applicants to upload a resume or use a LinkedIn profile to pre-populate the online application.

All positions are security-sensitive. Applicants are subject to a criminal history investigation, and employment is contingent upon the institution’s verification of credentials and/or other information required by the institution’s procedures, including the completion of the criminal history check.

Equal Opportunity/Affirmative Action/Veterans/Disability Employer.