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Texas A&M University Health Sciences Center

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Postdoctoral Research Associate in Occupational Health, Biomechanics, and Wearable Sensor Research Texas A&M University Health Science Center in United States

Degree Level

Postdoc

Field of study

Computer Science

Funding

Full-time staff postdoctoral position with salary commensurate with qualifications. Employee benefits include medical, prescription, dental, vision, life and accidental-death insurance, flexible spending accounts, long-term disability insurance, paid holidays, sick and vacation leave, retirement enrollment in the Teacher Retirement System of Texas, wellness programs, professional development support, and employee tuition assistance.

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Country

United States

University

Texas A&M University Health Sciences Center

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Keywords

Computer Science
Environmental Science
Biomedical Engineering
Mechanical Engineering
Deep Learning
Occupational Health
Industrial Engineering
Computer Vision
Ergonomics
Environmental Health
Salud Pública
Motion Capture
ML

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About this position

Texas A&M University Health Science Center is seeking a full-time Postdoctoral Research Associate in College Station, Texas, within the Department of Environmental and Occupational Health. The researcher will support occupational health studies in the Douphrate and Kim laboratories, investigating work-related exposures and their relationships with adverse health outcomes.

Responsibilities include managing externally funded field and laboratory projects; developing research protocols; collecting and analyzing data; training research staff and students; mentoring student research; coordinating with laboratory directors David Douphrate and Jay Kim; preparing proposals and manuscripts; presenting findings; and supporting administrative activities such as IRB processes, procurement, and project budgets.

The research uses 3-D motion capture, wearable and inertial sensors, electromyography, force plates, load cells, computer vision, biomechanical modeling, and software including OpenSim, Visual 3D, and Anybody. Experience with machine learning, deep learning, programming, survey analysis, and quantitative research is highly valued.

Applicants must hold a PhD in Environmental and Occupational Health, Biomechanics, Industrial Engineering, or a related field. At least three years of laboratory experience is preferred. The full-time staff position offers salary commensurate with qualifications and a comprehensive employee benefits package, including health insurance, paid leave, retirement participation, professional development, and tuition assistance. Applications should include complete job application information or a complete resume and must be submitted through the Texas A&M Workday portal.

Funding details

Full-time staff postdoctoral position with salary commensurate with qualifications. Employee benefits include medical, prescription, dental, vision, life and accidental-death insurance, flexible spending accounts, long-term disability insurance, paid holidays, sick and vacation leave, retirement enrollment in the Teacher Retirement System of Texas, wellness programs, professional development support, and employee tuition assistance.

What's required

Applicants must hold a PhD in Environmental and Occupational Health, Biomechanics, Industrial Engineering, or a related field. Preferred qualifications include expertise in 3-D motion capture systems and biomechanical modeling using OpenSim, Visual 3D, or Anybody; strong analytic, quantitative, programming, interpersonal, written and verbal communication, problem-solving, professionalism, and attention-to-detail skills; at least three years of laboratory experience; machine learning and deep learning modeling; and survey data collection and analysis. Applicants must submit complete application data or a complete resume, and employment is contingent on credential verification and a criminal history investigation.

How to apply

Apply through the Texas A&M University System Workday posting. Enter all required job application data or attach a complete resume; applicants may also use a LinkedIn profile to pre-populate the application.

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