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University of New Mexico

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PhD in Civil Engineering: Geomechanics, Computational Mechanics, Fracture and Damage Mechanics, and AI/Data-Driven Methods University of New Mexico in United States

Degree Level

PhD

Field of study

Computer Science

Funding

The position is expected to include PhD funding, subject to admission and university requirements.

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Country

United States

University

University of New Mexico

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Keywords

Computer Science
Mechanical Engineering
Materials Science
Artificial Intelligence
Civil Engineering
Structural Engineering
Geotechnical Engineering
Earth Science
Computational Mechanics
Geomechanics
Infrastructure Management
Fracture Mechanics
Damage Mechanics
Applied Mechanics
Natural Hazard
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About this position

PhD opportunity at the Gerald May Department of Civil, Construction and Environmental Engineering, University of New Mexico (Albuquerque, NM, USA).

The project is interdisciplinary and sits at the intersection of geomechanics, computational mechanics, fracture and damage mechanics, and data-driven / AI approaches. Research applications include geomaterials, infrastructure, and natural hazards.

Preferred backgrounds include Civil Engineering, Geotechnical Engineering, Structural Engineering, Mechanical Engineering, Engineering Mechanics, or related fields. Experience with numerical modeling, programming, laboratory testing, or machine learning is welcome, but not required.

The position is expected to include PhD funding, subject to admission and university requirements.

To apply, interested candidates should email the poster with a CV, academic transcripts, and a short description of research interests and relevant experience.

Funding details

The position is expected to include PhD funding, subject to admission and university requirements.

What's required

Applicants should have a background in Civil Engineering, Geotechnical Engineering, Structural Engineering, Mechanical Engineering, Engineering Mechanics, or a related field. Experience with numerical modeling, programming, laboratory testing, or machine learning is welcome but not required. Admission and university requirements apply.

How to apply

Interested candidates should contact the poster by email and send a CV, academic transcripts, and a brief description of research interests and relevant experience.

More information can be found here

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