Research Associate (Machine Learning)

Location: Onsite at the TTI RELLIS campus in Bryan, Texas; no hybrid remote option is available. The role requires periodic travel for routine fieldwork and data collection, comprising over 50% of the total work effort.

Company

Texas A&M Transportation Institute is a Texas state agency and member of The Texas A&M University System that develops research-based transportation solutions.

What you will do

• Conduct fieldwork and collect transportation and pavement-related data.
• Process, analyze, synthesize, and quality-check research data.
• Develop machine learning programs and algorithmic code, primarily using Python.
• Build computational models and perform numerical simulations.
• Conduct literature reviews, data searches, documentation, and report or proposal writing.
• Perform laboratory work and material testing while supporting senior researchers and student workers.

Requirements

• Bachelor’s degree in a relevant field.
• At least two years of related experience.
• Ability and flexibility to travel routinely for fieldwork, including work beyond normal business hours, weekends, or nights when needed.
• Proficiency with automation tools such as Python and Microsoft Office.
• Valid USA Class C driver’s license or ability to obtain one within 30 days of employment.
• Ability to lift and exert force of up to 50 pounds as needed.

Nice to have

• Bachelor’s degree in engineering, preferably Civil Engineering.
• Experience with fieldwork and data analysis.
• Experience with Python coding and machine learning programming.

Culture & Benefits

• Entrepreneurial work environment affiliated with Texas A&M University students and faculty.
• Access to recognized transportation experts, research facilities, accredited laboratories, and a safety proving ground.
• Flexible work hours and a family-friendly environment.
• Health coverage options and additional employee benefit programs.
• Data allowance, home office equipment reimbursements, leadership development, and wellness programs.
• Relocation assistance and tuition reimbursement may be available if eligible.

Hiring process

• Further discussion of the position and work arrangement may take place during the interview process.
• Employment is contingent upon satisfactory performance, funding availability, credential verification, and completion of a criminal history investigation.