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Prairie View A&M University

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Postdoctoral Researcher (Artificial Intelligence) Prairie View A&M University in United States

Degree Level

Postdoc

Field of study

Computer Science

Funding

Funded by restricted or grant funds; continued employment depends on the availability and renewal of funding. Salary is commensurate with education and experience within the assigned salary range.

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Country

United States

University

Prairie View A&M University

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Keywords

Computer Science
Mechanical Engineering
Electrical Engineering
Materials Science
Deep Learning
Artificial Intelligence
Computer Vision
Additive Manufacturing
Statistics
Ct Imaging
ML

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About this position

This postdoctoral appointment at Prairie View A&M University sits within an interdisciplinary research effort in artificial intelligence and machine learning for metal additive manufacturing. The project focuses on Electron Beam Powder Bed Fusion (E-PBF) of refractory alloys, combining process monitoring, microstructure modeling, and AI-driven control.

The researcher will work on in-situ backscattered electron (BSE) microstructure sensing and use time-resolved process data to develop predictive models of microstructure evolution. The work also includes X-ray computed tomography (XCT) image processing and analysis to characterize internal defects and to support validation of machine-learning predictions and monitoring results.

The role is strongly computational and data-centric. The appointee will contribute to data engineering, high-resolution scientific image and sequence analysis, deep learning model development, benchmarking, real-time prediction and control, and reproducible research software. Methods development will include transformer-based and other sequence-learning architectures, as well as workflows that connect process parameters, in-situ observations, and resulting microstructural features.

The postdoctoral researcher will also take part in research leadership activities within the group, including helping coordinate project components, documenting datasets and workflows, and contributing to a codebase and research repository. The position includes collaborative work with engineering and materials-science researchers, plus opportunities to support manuscript preparation, proposals, technical reports, presentations, and broader scholarly outputs.

In addition to independent research, the appointee will help mentor undergraduate and graduate students and assist with supervision activities in coordination with the principal investigator and project team.

Funding details

Funded by restricted or grant funds; continued employment depends on the availability and renewal of funding. Salary is commensurate with education and experience within the assigned salary range.

What's required

A Ph.D. in Computer Science, Electrical or Computer Engineering, Mechanical Engineering, Materials Science and Engineering, Data Science, Applied Mathematics, or a closely related discipline is required. Applicants should have at least one year of research experience applying machine learning, deep learning, computer vision, scientific data analytics, or related data-driven methods. Strong programming skills in Python and experience with machine learning libraries such as PyTorch, TensorFlow, scikit-learn, and Keras are required, along with knowledge of machine learning, deep learning, data analytics, and model evaluation. Experience with data processing pipelines, statistical analysis, and data visualization tools including matplotlib, seaborn, and Plotly is expected. Strong written and verbal communication skills, the ability to collaborate with multidisciplinary teams, and a record of contributing to peer-reviewed publications are required.

How to apply

Apply through the PVAMU Career Site before the posting closes. Upload a resume or CV and a cover letter with the application. Direct email or website inquiries will not be considered unless you have applied through the career site; contact [email protected] or 936-261-1730 for application assistance.

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