Graduate Employee-Dept of Engineering Technology-Research Associate
- Sam Houston State University
- Huntington, West Virginia
- Full Time
Posting Details
Posting Information
Requisition202500229ST
TitleGraduate Employee-Dept of Engineering Technology-Research Associate
Employee ClassGraduate Employee
College Work Study PositionNo
DepartmentDept of Engineering Technology
DivisionDivision of Academic Affairs
Hours per week20
Hiring Rate
Salary = $19,000 (fixed term)
Preferred Student Classification
Background in Mechanical Engineering/ Computer Science/ Applied Mathematics, or a related field.
Strong programming skills in Python; experience with ML frameworks such as PyTorch or TensorFlow.
Familiarity with CAD/3D modeling tools.
Exposure to additive manufacturing and experience with 3D printing workflows is a plus.
Demonstrated interest or experience in physics-informed machine learning is highly desirable.
Nature & Purpose of Position
We are seeking a highly motivated and technically skilled Research Associate to support an interdisciplinary project at the intersection of artificial intelligence, physics modelling, and additive manufacturing. The project is centered on developing and validating novel AI-based frameworks (Physics Informed Neural Networks - PINNs) that enhance the efficiency and reliability of design evaluation and rapid prototyping workflows.
This research role is ideal for candidates with a strong foundation in machine learning or physics-based modeling, who are interested in applying their skills to practical challenges in next-generation manufacturing.
Responsibilities:
Assist in the development of a PINNs to evaluate complex design geometries.
Contribute to simulation workflows that integrate SciML for assessing structural performance under uncertainty.
Collaborate in prototyping and experimental validation of the designs using additive manufacturing techniques.
Support dataset preparation, model training and evaluation, and the development of visual or analytical reporting tools.
Participate in regular research meetings and contribute to the preparation of research manuscripts and reports.
Other Requirements for the Position
Key Competencies:
Strong analytical and problem-solving skills.
Self-motivated and able to work independently in research setting.
Effective communication skills and willingness to work in a collaborative environment.
Project Context:
The appointed researcher will work on a cutting-edge initiative aimed at accelerating design validation through machine learning and simulation-informed AI models. While specific project details are confidential, the work broadly addresses current challenges in reducing computational burdens and design cycle times in advanced manufacturing processes.
Open Date05/21/2025
Position Number9N9944-00
Contact Information
Contact Name & TitleDr. Syed Hasib Akhter Faruqui, Assist Prof - Engineering Design
Contact Phone...
Contact ...
Contact Building & Room #Pirkle 324
Contact Fax
Contact Instructions Summary
EEO Statement
EEO Statement
Sam Houston State University is an Equal Employment Opportunity Employer and Smoke/Drug-Free Workplace. All qualified applicants will receive consideration for employment without regard to race, creed, ancestry, marital status, citizenship, color, national origin, sex, religion, age, disability, or protected veteran status. The University takes seriously the initiative to ensure equal opportunity in the workforce and to comply with Title VII as interpreted by the U.S. Supreme Court. Sam Houston State University is an at will employer. Employees with a contract will have additional terms and conditions. Security-sensitive positions at SHSU require background checks in accordance with Education Code 51.215.
Annual Security and Fire Safety Report
Posting Information
Requisition202500229ST
TitleGraduate Employee-Dept of Engineering Technology-Research Associate
Employee ClassGraduate Employee
College Work Study PositionNo
DepartmentDept of Engineering Technology
DivisionDivision of Academic Affairs
Hours per week20
Hiring Rate
Salary = $19,000 (fixed term)
Preferred Student Classification
Background in Mechanical Engineering/ Computer Science/ Applied Mathematics, or a related field.
Strong programming skills in Python; experience with ML frameworks such as PyTorch or TensorFlow.
Familiarity with CAD/3D modeling tools.
Exposure to additive manufacturing and experience with 3D printing workflows is a plus.
Demonstrated interest or experience in physics-informed machine learning is highly desirable.
Nature & Purpose of Position
We are seeking a highly motivated and technically skilled Research Associate to support an interdisciplinary project at the intersection of artificial intelligence, physics modelling, and additive manufacturing. The project is centered on developing and validating novel AI-based frameworks (Physics Informed Neural Networks - PINNs) that enhance the efficiency and reliability of design evaluation and rapid prototyping workflows.
This research role is ideal for candidates with a strong foundation in machine learning or physics-based modeling, who are interested in applying their skills to practical challenges in next-generation manufacturing.
Responsibilities:
Assist in the development of a PINNs to evaluate complex design geometries.
Contribute to simulation workflows that integrate SciML for assessing structural performance under uncertainty.
Collaborate in prototyping and experimental validation of the designs using additive manufacturing techniques.
Support dataset preparation, model training and evaluation, and the development of visual or analytical reporting tools.
Participate in regular research meetings and contribute to the preparation of research manuscripts and reports.
Other Requirements for the Position
Key Competencies:
Strong analytical and problem-solving skills.
Self-motivated and able to work independently in research setting.
Effective communication skills and willingness to work in a collaborative environment.
Project Context:
The appointed researcher will work on a cutting-edge initiative aimed at accelerating design validation through machine learning and simulation-informed AI models. While specific project details are confidential, the work broadly addresses current challenges in reducing computational burdens and design cycle times in advanced manufacturing processes.
Open Date05/21/2025
Position Number9N9944-00
Contact Information
Contact Name & TitleDr. Syed Hasib Akhter Faruqui, Assist Prof - Engineering Design
Contact Phone...
Contact ...
Contact Building & Room #Pirkle 324
Contact Fax
Contact Instructions Summary
EEO Statement
EEO Statement
Sam Houston State University is an Equal Employment Opportunity Employer and Smoke/Drug-Free Workplace. All qualified applicants will receive consideration for employment without regard to race, creed, ancestry, marital status, citizenship, color, national origin, sex, religion, age, disability, or protected veteran status. The University takes seriously the initiative to ensure equal opportunity in the workforce and to comply with Title VII as interpreted by the U.S. Supreme Court. Sam Houston State University is an at will employer. Employees with a contract will have additional terms and conditions. Security-sensitive positions at SHSU require background checks in accordance with Education Code 51.215.
Annual Security and Fire Safety Report
Job ID: 478400859
Originally Posted on: 5/25/2025
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