Tenure-Track Geospatial Engineering for Civil Innovation

Lamar-University; Beaumont (TX); On-site; USD 90,000 - 120,000; Full time

Benefits offered by this job

Health, dental & vision insurance

Life insurance

State of Texas Retirement plans

Tuition covered at 100% for employees,

spouses and/or eligible dependents

Paid time off – vacation, sick, andhol

Job summary

Lamar University is inviting applications for a tenure-track Assistant Professor in geospatial engineering in the Department of Civil and Environmental Engineering. The role focuses on teaching, research, and service, with 40% teaching, 50% research, and 10% service workload.

The candidate should have expertise in remote sensing, GIS, LiDAR, and digital twins, and pursue external funding. The successful candidate will teach multiple courses each semester, mentor students, and develop field, lab,

Qualifications

• Earned Ph.D. in civil engineering or closely related field by start date.
• Ability to teach multiple courses each semester in geospatial engineering.
• Professional Engineer (PE) license or documented pathway to licensure.
• Strong communication and collaboration skills and potential to establish externally funded research.

Responsibilities

• Teach multiple undergraduate/graduate courses in surveying, GIS, remote sensing, and geospatial apps.
• Establish and sustain an externally funded geospatial engineering research program with industry/public partnerships.
• Contribute to departmental, college, university, and professional service and outreach.

Skills

Geospatial methods

GIS

Remote sensing

Surveying/Geomatics

LiDAR

3D visualization

Digital twins

Communication

Collaboration

Education

Ph.D. in civil engineering or closely related field

Tools

ArcGIS

QGIS

LiDAR processing software

Job description

Lamar University is inviting applications for a tenure-track Assistant Professor in geospatial engineering in the Department of Civil and Environmental Engineering. The role focuses on teaching, research, and service, with 40% teaching, 50% research, and 10% service workload.

The candidate should have expertise in remote sensing, GIS, LiDAR, and digital twins, and pursue external funding. The successful candidate will teach multiple courses each semester, mentor students, and develop field, lab,