Postdoctoral Fellow

Colorado State University • Fort Collins, CO

1d • Onsite

About The Position

To advance the Department of Construction Management’s strategic priorities in innovation, technology infusion, and high-impact scholarship, this Postdoctoral Fellow position focuses on digital technologies, automation, artificial intelligence (AI), and robotics as applied to construction and the built environment. The role is designed to be flexible with evolving faculty research needs and emerging industry directions, with three core deliverables: research enablement, targeted teaching support, and curriculum/module development. The postdoc will enhance the department’s capacity to accelerate externally visible research outputs (papers, proposals, datasets), strengthen instruction in quantitative decision-making and AI-adjacent methods, and produce concrete curriculum development outputs by creating AI/digital-technology/automation modules, labs, and applied case materials for existing CM courses. The Department of Construction Management at Colorado State University is one of the largest programs in the country, serving approximately 800 undergraduate students, 15-20 graduate students, 21 faculty, and 7 professional staff. It offers bachelor's and master's degrees in construction management and collaborates with other departments for interdisciplinary Ph.D. programs. The undergraduate program is accredited by the American Council for Construction Education, and the department provides academic advising, internship, and career placement support. Facilities include over 36,000 square feet of dedicated labs, classrooms, and offices.

Requirements

• Earned PhD in Construction Management, Civil Engineering, Industrial Engineering, or related field with demonstrated relevance to construction/built environment applications.
• Demonstrated research capability and productivity (e.g., publications, proposal record).
• Technical competence in one or more relevant areas (e.g., machine learning/AI, data analytics, robotics/automation, digital twins/IoT, optimization/decision analytics, multi-criteria decision-making).
• Interest and ability to support teaching and contribute to curriculum development.
• Teaching/TA experience and/or curriculum/module development experience.
• Mentoring experience with graduate students or project teams.
• Minimum required years of experience: 1

Responsibilities

• Execute applied research workflows that accelerate faculty scholarship in digital technologies, automation, AI, and robotics for construction.
• Design and implement data collection/curation, modeling and validation pipelines, and reproducible computational artifacts that directly enable publications, proposals, and externally visible research outcomes.
• Co-develop peer-reviewed research products and proposal-ready deliverables.
• Draft and iterate proposal sections, figures/tables, results narratives, and technical appendices; prepare preliminary analyses and prototypes that strengthen competitiveness for external funding and shorten the cycle time from idea to submission.
• Support delivery of the Multi Criteria Decision-Making course through targeted instructional assistance.
• Develop applied examples, datasets, and learning activities aligned with construction decision contexts; provide structured student support (e.g., labs/recitations, office hours, assignment support, grading assistance as defined by the instructor) to improve learning outcomes and instructional consistency.
• Develop AI and digital technology curriculum modules that can be embedded across Construction Management courses.
• Produce modular content (1–3 week units), hands-on labs/tutorials, case studies, and assessment tools (rubrics, concept checks, applied deliverables) that institutionalize technology infusion into the curriculum.
• Mentor and coordinate with graduate students supporting technical project execution.
• Provide guidance on research methods, data practices, and documentation standards; support effective task planning and quality control to ensure timely progress toward publishable outcomes.
• Perform related responsibilities as assigned to support departmental research and instructional priorities.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree
• Number of Employees: 1-10 employees