Strong academic background in one or more of the following areas: probability and statistics, design of experiments, operations research/prescriptive analytics (exact, heuristic and simulation methods), productivity analysis (i.e., facilities planning, quality engineering, production systems, methods engineering, lean manufacturing, project management, supply chain engineering), human factors, engineering economics, and computational data analytics. Classified as a Carnegie Doctoral University with High Research Activity (R2), TXST is actively advancing its ambitious Run to R1 strategy, demonstrating sustained growth in research activity, doctoral education, and scholarly impact.