Postdoctoral Scholar
Ensured Consideration Date: August 1, 2026
Michigan Technological University is an R1 technological research university founded in 1885 in Houghton. Our rural campus is situated just miles from Lake Superior in Michigan's scenic Upper Peninsula and is home to nearly 7,500 students from more than 60 countries around the world. Consistently ranked among the best universities in the country for return on investment, Michigan’s flagship technological university offers more than 185 undergraduate and graduate degree programs. Research focus areas include defense, health, energy, automotive, environment, and aerospace.
The area’s waters, forests, and snowfall support year-round recreation, including skiing, snowboarding, hiking, biking, and paddling. The University is an integral part of the region, supported by a friendly and welcoming community that takes pride in being a true college town. We embrace our size, climate, sense of adventure, and originality.
Summary
Professor M. Emin Kutay’s research group in the Department of Civil, Environmental, and Geospatial Engineering at Michigan Technological University is seeking a motivated postdoctoral research associate to advance the analysis, quality assurance, and calibration of automated pavement condition data and pavement performance modeling. The successful candidate will contribute to two sponsored research projects: (1) development of an improved calibration and data quality management framework for automated pavement distress collection and processing for the Minnesota Department of Transportation (MnDOT); and (2) validation and recalibration of the Pavement Distress Score (PDS) and associated pavement condition indices and deterioration models for the Michigan Department of Transportation (MDOT). This position is supported by the Minnesota Department of Transportation (MnDOT) and the Michigan Department of Transportation (MDOT).
Responsibilities and Essential Duties
Performing research across two sponsored projects, including: developing and applying statistically based calibration, audit, and validation procedures for automated pavement distress data collection systems; evaluating and recalibrating pavement distress definitions, severity thresholds, distress weight factors, and composite pavement condition indices; assessing pavement deterioration models and network-level condition projection methods; developing and maintaining data analysis tools and processing pipelines in Python; helping with proposal preparation; preparing manuscripts for publication in peer-reviewed journals; and supervising and collaborating with graduate and undergraduate students.
Required Education, Certifications, Licensures
Ph.D. in Civil Engineering. The degree must have been earned within 72 months prior to the beginning of the appointment.
Required Experience
- Six (6) years of research experience in at least three (3) of the following research areas: civil engineering, pavement engineering, pavement distress data collection and analysis, pavement management systems, statistical data analysis, and mechanistic-empirical pavement modeling.
- Experience in publishing research findings in top peer-reviewed journals.
Desirable Education and/or Experience
Strong background in mechanistic-empirical pavement design and asphalt viscoelasticity is desired. Experience with automated pavement distress data, pavement condition indices, or pavement management software is also desirable.
Required Knowledge, Skills, and/or Abilities
Demonstrated ability to communicate effectively across cultural boundaries and work harmoniously with diverse groups of students, faculty, and staff. Strong programming skills in Python.
Desirable Knowledge, Skills, and/or Abilities
- Knowledge of pavement engineering, mechanistic-empirical pavement design, asphalt viscoelasticity, pavement distress and condition data, statistical analysis methods, and pavement management systems.
- Language, Mathematics and/or Reasoning Skills: familiarity with the JAVA programming language is desirable; strong mathematical, statistical, and analytical reasoning skills.
Work Environment and/or Physical Demands
The work environment is that of a typical lab or office setting. The noise level in the work environment is usually low to moderate.
Required Training and Other Conditions of Employment
Every employee at Michigan Technological University will receive the following 4 required trainings; additional training may be required by the department.
Required University Training:
• Employee Safety Overview
• Anti-Harassment, Discrimination, Retaliation Training
• Annual Data Security Training
• Annual Title IX Training
Background Check:
Offers of employment are contingent upon and not considered finalized until the required background check has been performed and the results received and assessed.
J-1 visa sponsorship is available for this position. This is not an E-Verified position. Appointment term: 12 months (renewable, dependent on funding). FLSA status: Exempt. FTE: 100%.
Full-Time Equivalent (FTE) % (1=100%): 1
FLSA Status: Exempt
Appointment Term: 12 months
Pay Rate/Salary: The salary range for this position is $55,000 - $58,000. However, the final salary will depend on experience and qualifications.
Title of Position Supervisor: Department Chair
Posting Type: Internal & External
Dependent on Funding: No
Additional Information: Full ensured consideration will be given to applicants who apply on or before August 1, 2026
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