Posting Number:

req25668

Department:

Systems and Industrial Engr Location:

Tucson Campus Address:

1127 E. James E. Rogers Way, Tucson, AZ 85721 USA Position Highlights The Department of Systems and Industrial Engineering seeks a Postdoctoral Research Associate to support research at the intersection of systems engineering and digital engineering, with an emphasis on advancing methods, tools, and architectures that enable modern engineering practice. The individual will contribute original scholarship and applied research, developing prototypes and capabilities that strengthen model-based and data-driven approaches. The position values interdisciplinary thinking, particularly where software development, emerging AI-enabled techniques, and systems modeling intersect. Responsibilities include publishing and presenting research results while helping shape and mature a digital engineering sandbox environment. Outstanding U of A benefits include health, dental, vision, and life insurance; paid vacation, sick leave, and holidays; U of

A/ASU/NAU

tuition reduction for the employee and qualified family members; access to U of A recreation and cultural activities; and more! The University of Arizona has been recognized for our innovative work-life programs. For more information about working at the University of Arizona and relocations services, please click here . Duties & Responsibilities Author and co-author peer-reviewed journal papers targeting venues such as Systems Engineering (Wiley/INCOSE), SIMULATION (SCS/SAGE), Applied Ontology (IOS Press), and relevant

IEEE/ACM

journals. Prepare and present conference papers at

CSER, INCOSE

IS, CESUN, and similar venues. Contribute to technical reports and sponsor deliverables as needed. Support the design and implementation of a digital engineering sandbox environment for capability prototyping, training, and experimentation. Integrate emerging SE tooling (e.g., AI-assisted workflows, ontology-backed reasoning, requirements co-pilots) into the sandbox. Ensure the sandbox supports controlled experimentation and repeatable demonstrations of SE capabilities. Design, implement, and evaluate next-generation SE capabilities such as AI-augmented requirements engineering, automated conflict detection, model-based review support, and change impact analysis. Advance selected capabilities from early maturity toward cross-context application using the project's assessment framework. Prototype and test novel capability concepts informed by the transformation roadmap and sponsor priorities. Conduct systematic literature reviews on digital engineering transformation, AI-augmented systems engineering, readiness assessment frameworks, and formal methods for SE. Monitor and synthesize emerging SE capabilities. Maintain a living literature database supporting project deliverables and journal submissions. Design and execute controlled experiments, case studies, interviews, or surveys to generate rigorous evidence on SE capability effectiveness. Collect and analyze data from sponsors and stakeholders on adoption barriers, governance gaps, and capability value. Engage with professional organizations (e.g., INCOSE) to solicit expert feedback on the transformation roadmap framework and assessment methodology. Mentor and supervise undergraduate research assistants working on project tasks. Define scoped research tasks appropriate for undergraduate contribution (literature coding, data collection, prototype testing, documentation). Review student work products and support their professional development (conference presentations, writing skills, research methods). Knowledge, Skills, and Abilities Knowledge of systems engineering principles, including model-based systems engineering (MBSE). Knowledge of digital engineering concepts, tools, and transformation initiatives. Skilled in utilizing Python. Minimum Qualifications Ph.D. in Systems Engineering, Computer Science, Industrial Engineering, or a closely related field. The selected candidate must have a conferred Ph.D. upon hire. Experience publishing peer-reviewed journals and conference papers (e.g., IEEE, ACM, or comparable venues). Experience designing and implementing research prototypes or software tools. Preferred Qualifications Experience with model-based systems engineering tools (e.g., SysML, Cameo, MagicDraw, Capella). Demonstrate familiarity with digital engineering ecosystems and sandbox/testbed environments. Experience with AI/ML techniques applied to systems engineering problems (e.g., requirements analysis, reasoning, automation). Experience in ontology engineering, knowledge graphs, or semantic technologies. Experience integrating heterogeneous tools and workflows (e.g., APIs, co-simulation, digital threads).

FLSA:

Exempt Full Time/Part Time:

Full Time Number of Hours Worked per

Week:

Job FTE:

1.0

Work Calendar:

Fiscal Job Category:

Research Benefits Eligible:

Yes -

Full Benefits Rate of Pay:

NIH salary guidelines, Depends on

Experience Compensation Type:

salary at 1.0 full-time equivalency (FTE) Type of criminal background check required: Name-based criminal background check (non-security sensitive)

Number of Vacancies:

1 Contact Information for Candidates Alejandro Salado alejandrosalado@arizona.edu

Open Until Filled:

Yes Documents Needed to

Apply:

Curriculum Vitae (CV) and Cover Letter Notice of Availability of the Annual Security and Fire Safety Report In compliance with the Jeanne Clery Campus Safety Act (Clery Act), each year the University of Arizona releases an Annual Security Report (ASR) for each of the University's campuses. These reports disclose information including Clery crime statistics for the previous three calendar years and policies, procedures, and programs the University uses to keep students and employees safe, including how to report crimes or other emergencies and resources for crime victims. As a campus with residential housing facilities, the Main Campus ASR also includes a combined Annual Fire Safety report with information on fire statistics and fire safety systems, policies, and procedures. 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Postdoctoral Research Associate, Systems and Industrial Engineering