Research Assistant (Data Analysis, Industrial & Systems Engineering)

The Research Assistant supports a grant-funded research project within the College of Engineering and the Department of Computer Sciences by collecting, analyzing, and interpreting complex datasets. This position applies machine learning, computer vision, and data-driven modeling techniques, and contributes to technical reports, presentations, and research publications. The Research Assistant collaborates closely with faculty, graduate students, and interdisciplinary research teams., * Data Collection, Cleaning, and Management (30%)

• Data Analysis and Modeling (25%)
• Visualization and Reporting (15%)
• Research Support and Documentation (15%)
• Collaboration and Meetings (10%)
• Dissemination and Administrative Support (5%)

Currently enrolled in a master’s or doctoral (DE) program in Engineering, Computer Science, Mathematics, Statistics, Data Science, or a related quantitative field., * Demonstrated experience with data analysis tools such as Python, R, MATLAB, or SQL

• Experience working with large datasets, including data cleaning, transformation, and exploratory analysis
• Strong written and oral communication skills to document findings, present results to faculty and team members, and contribute to journal publications

Desired Qualifications

• Prior experience with machine learning, predictive modeling, or clustering techniques
• Experience with data visualization tools and techniques, * Ability to analyze and interpret complex datasets to support engineering research objectives
• Programming skills for data analysis, including writing efficient and well-documented code
• Data visualization and reporting skills
• Collaborative teamwork skills, with the ability to work effectively with faculty, graduate students, and interdisciplinary research teams

Physical Requirements

Ability to lift up to 25 pounds and perform a variety of physical tasks, including lifting, bending, stooping, squatting, stair climbing, and walking between buildings. Job Conditions

Appointment is contingent upon funding and satisfactory performance and may be renewed each semester or academic year.

Lamar University is An Equal Opportunity Employer

Lamar University is proud to provide employment preference to veteran applicants in accordance with Texas 805 Government Code, Section 657.003.

This position is security-sensitive and thereby subject to the provisions of the Texas Education Code §51.215, which authorizes the employer to obtain criminal history record information.