Research Scientist

JOB SUMMARY:

This role focuses on designing and implementing advanced control systems that seamlessly integrate uncertainty quantification across modeling, simulation, and decision making workflows. It requires applying rigorous ASME aligned verification and validation practices to ensure model credibility and reliability in diverse engineering contexts. The position leverages AI and machine learning to enhance system performance while rigorously characterizing uncertainty, validating data driven components, and assessing the robustness of autonomous decision processes. Collaboration with faculty, students, visiting researchers, and industry partners—particularly those engaged with Clemson’s MV test facility—is central, with an emphasis on VVUQ driven experimental design, model refinement, and system level evaluation

JOB DUTIES:

50% - Design, develop, and implement advanced control systems that operate under uncertainty, integrating uncertainty quantification into modeling, simulation, and real‑time decision workflows supported by high‑performance computing. Apply rigorous verification and validation practices—aligned with ASME V&V methodologies—to ensure model credibility, assess numerical accuracy, and establish confidence in both physics‑based and data‑driven components. Leverage AI and ML techniques to enhance the performance, efficiency, and scalability of control systems while systematically characterizing model uncertainty, validating learning‑enabled elements, and evaluating robustness across diverse engineering domains, including renewable energy technologies, electric transportation, industrial automation, and other complex engineered systems.

20% - Provide oversight, guidance, and mentoring to student interns and graduate students, emphasizing best practices in uncertainty quantification, model verification, and validation to ensure credible and trustworthy computational and experimental work. Maintain strict industry confidentiality and ensure secure handling of equipment, data, and models, including the protection of validation datasets and sensitive uncertainty analyses. Build strong, VVUQ‑aware relationships with industry partners to support collaborative research, model‑credibility assessments, and educational engagement. Ensure full compliance with all federal and state safety and environmental regulations, integrating verification and validation principles into laboratory procedures, experimental protocols, and risk‑informed decision‑making.

30% - Stay current with emerging developments in AI and ML, and apply new techniques to advance control systems while incorporating rigorous uncertainty quantification, verification, and validation practices consistent with ASME V&V methodologies. Continuously evaluate the credibility and robustness of both physics‑based and data‑driven models, ensuring that new computational approaches meet established standards for model accuracy, reliability, and uncertainty management across diverse engineering applications. Pursue competitive grant funding that leverages the capabilities of the CURI campus, emphasizing VVUQ‑driven research themes, and actively work toward publishing in peer‑reviewed journals that highlight contributions in model validation, uncertainty quantification, and trustworthy computational engineering.

JOB CODE:

UK07

EMPLOYEE TYPE:

Time-Limited (TLP) Staff

Design, develop, and implement advanced control systems, integrating uncertainty quantification throughout modeling, simulation, and decision‑making workflows. Apply rigorous verification and validation practices—consistent with ASME V&V principles—to ensure model credibility, reliability, and traceability across diverse engineering applications. Leverage AI and ML techniques to enhance the performance, efficiency, and scalability of control systems while systematically characterizing model uncertainty, validating data‑driven components, and assessing the robustness of autonomous decision processes. Collaborate closely with faculty, students, visiting researchers, and industry partners engaged with Clemson’s MV test facility, emphasizing VVUQ‑driven methodologies in experimental design, model refinement, and system‑level evaluation.

RESPONSIBILITIES:

JOB KNOWLEDGE

Firm working knowledge of concepts, practices and procedures and ability to use in varied situations.

SUPERVISORY RESPONSIBILITIES

Acts as a Lead by guiding the work of others who perform essentially the same work.

BUDGETARY RESPONSIBILITIES

Fiscal Responsibilities: Fiscal responsibilities for the department's budget, including but not limited to, financial planning and managing fund allocation

PHYSICAL REQUIREMENTS:

Recognize or inspect visually: 10%
Extends hands or arms in any direction: 5%
Sit (stationary position) for prolonged period: 10%
Use hands or feet to operate or handle machinery, equipment, etc.: 10%
Position self to accomplish task (i.e. stoop, kneel, crawl): 10%
Communicate, converse, give direction, express oneself: 10%
Walk or move about: 10%
Move, transport, raise or lower 50 lbs or more: 5%
Stand for Prolonged Period: 10%
Move, transport, raise or lower 30lbs or less: 10%
Perceive, observe, clarity of vision: 10%
Ascend or descend (i.e. stairs, ladder): 10%

WORKING CONDITIONS:

Wet and/or humid: 20%
Exposure to heat or cold: 20%
Noise: 10%
Mechanical hazards: 20%
Electrical hazards: 30%

WORK SCHEDULE:

Standard Hours:

37.5

COMPENSATION INFORMATION:

Expected Salary Range

67765 - 90000

Salary is dependent upon several factors including, but not limited to, a candidate's previous experience, knowledge, skills and performance in accordance with Clemson's compensation guidelines.

ESSENTIAL PERSONNEL LEVEL:

Normal Operations - Required to follow emergency facility closure and modified operations directives, and not normally expected to work on-site during emergency situations.

JOB LOCATION:

North Charleston, SC

APPLICATION DEADLINE:

August 17, 2026

MILITARY AND VETERAN:

Military Equivalency: Clemson University is proud to allow educational equivalency for military technical certifications and trainings that directly relate to the job duties.

Veteran Preference: South Carolina provides employment preference to eligible veterans for qualifying full-time permanent positions. To be considered, applicants must meet the minimum qualifications, have been discharged under honorable conditions, and indicate their veteran status in the application by uploading a DD-214 for confidential review. A request for Veteran Preference can be made via the application process. Please contact [email protected] with any questions or issues.

CLOSING STATEMENT:

Clemson University is an EEO/AA employer. Employment decisions are made without regard to characteristics protected by applicable law including disability and protected veteran status.