University of New Hampshire
Research Associate (Part‑time, hourly) – Faculty‑led research in the Department of Civil and Environmental Engineering focusing on structural engineering, digital twinning, advanced computational modeling, and experimental validation.
Responsibilities Research Support (40%)
Conduct laboratory and field experiments on structural systems, including instrumentation, data collection, and test execution.
Perform structural modeling, simulation, and validation activities.
Assist with analysis of large‑scale experimental and monitoring data.
Support digital twin and machine‑learning–based methods for civil infrastructure.
Scholarly Contribution (25%)
Conduct literature reviews and summarize recent advances in structural engineering, digital twinning, and artificial intelligence applications.
Draft, edit, and prepare manuscripts for journal and conference submissions.
Assist in the preparation of research proposals and technical reports.
Programming & Data Analytics (20%)
Develop and implement algorithms for system identification, condition assessment, and structural health monitoring.
Apply statistical and computational tools to assess research hypotheses.
Mentoring & Collaboration (15%)
Provide guidance to undergraduate and graduate students involved in related projects.
Collaborate with faculty, postdoctoral researchers, and project partners on joint tasks.
Requirements Minimum Acceptable Education & Experience
Ph.D. in Civil Engineering, Structural Engineering, or a closely related field.
Demonstrated research experience in structural mechanics, structural health monitoring, experimental testing, or computational modeling.
Knowledge, Skills & Abilities
Strong background in structural analysis, system identification, and digital twinning.
Proficiency in MATLAB, Python, or similar computational tools.
Ability to design and conduct laboratory and/or field experiments, including instrumentation and data collection.
Ability to analyze and interpret experimental and monitoring data.
Excellent written and oral communication skills.
Ability to work independently and collaboratively within a research group.
Preferred Qualifications
Prior peer‑reviewed publications in structural health monitoring, system identification, or digital twin applications.
Experience with proposal writing and interdisciplinary collaboration.
Familiarity with machine learning methods and high‑performance computing applications in engineering.
Location: Durham
Salary Grade: Adjunct Hourly Staff 00
EEO Statement
The University System of New Hampshire is an Equal Opportunity/Equal Access employer. The University System is committed to creating an environment that values and supports diversity and inclusiveness across our campus communities and encourages applications from qualified individuals who will help us achieve this mission. The University System prohibits discrimination on the basis of race, color, religion, sex, age, national origin, sexual orientation, gender identity or expression, disability, genetic information, veteran status, or marital status.
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Responsibilities Research Support (40%)
Conduct laboratory and field experiments on structural systems, including instrumentation, data collection, and test execution.
Perform structural modeling, simulation, and validation activities.
Assist with analysis of large‑scale experimental and monitoring data.
Support digital twin and machine‑learning–based methods for civil infrastructure.
Scholarly Contribution (25%)
Conduct literature reviews and summarize recent advances in structural engineering, digital twinning, and artificial intelligence applications.
Draft, edit, and prepare manuscripts for journal and conference submissions.
Assist in the preparation of research proposals and technical reports.
Programming & Data Analytics (20%)
Develop and implement algorithms for system identification, condition assessment, and structural health monitoring.
Apply statistical and computational tools to assess research hypotheses.
Mentoring & Collaboration (15%)
Provide guidance to undergraduate and graduate students involved in related projects.
Collaborate with faculty, postdoctoral researchers, and project partners on joint tasks.
Requirements Minimum Acceptable Education & Experience
Ph.D. in Civil Engineering, Structural Engineering, or a closely related field.
Demonstrated research experience in structural mechanics, structural health monitoring, experimental testing, or computational modeling.
Knowledge, Skills & Abilities
Strong background in structural analysis, system identification, and digital twinning.
Proficiency in MATLAB, Python, or similar computational tools.
Ability to design and conduct laboratory and/or field experiments, including instrumentation and data collection.
Ability to analyze and interpret experimental and monitoring data.
Excellent written and oral communication skills.
Ability to work independently and collaboratively within a research group.
Preferred Qualifications
Prior peer‑reviewed publications in structural health monitoring, system identification, or digital twin applications.
Experience with proposal writing and interdisciplinary collaboration.
Familiarity with machine learning methods and high‑performance computing applications in engineering.
Location: Durham
Salary Grade: Adjunct Hourly Staff 00
EEO Statement
The University System of New Hampshire is an Equal Opportunity/Equal Access employer. The University System is committed to creating an environment that values and supports diversity and inclusiveness across our campus communities and encourages applications from qualified individuals who will help us achieve this mission. The University System prohibits discrimination on the basis of race, color, religion, sex, age, national origin, sexual orientation, gender identity or expression, disability, genetic information, veteran status, or marital status.
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