Western Carolina University
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Postdoc Research Scholar in Digital Twins and Federated Learning for Advanced Manufacturing Western Carolina University in United States
Degree Level
Postdoc
Field of study
Computer Science
Funding
Full-time, 12-month, time-limited, grant-funded postdoctoral appointment anticipated from about 2027-01-01 through 2029-06-30, with annual renewal contingent on satisfactory performance and continued funding. Salary is not specified in the post.
Country
United States
University
Western Carolina University

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About this position
Postdoc Research Scholar in Digital Twins and Federated Learning for Advanced Manufacturing at Western Carolina University (Department of Electrical and Computer Engineering).
This is a full-time, 12-month, time-limited, grant-funded postdoctoral appointment focused on digital twins, federated learning, and advanced manufacturing. The successful candidate will develop, calibrate, and validate digital twin simulation models for manufacturing equipment, processes, and material behavior; integrate machine learning into the digital twin and federated learning environment; and support evaluation and deployment at industry partner sites.
The role is part of a joint Western Carolina University and North Carolina State University research team and includes scholarly publications, project deliverables, student mentoring, curriculum modules, and hands-on training activities. The position reports to the project principal investigator and is located on-site in Cullowhee, North Carolina, with periodic travel to partner manufacturing sites in North Carolina. Remote work is not available.
Research keywords: digital twins, federated learning, modeling and simulation, uncertainty quantification, statistical validation, machine learning, Python, PyTorch, TensorFlow, embedded systems, edge computing, real-time control, privacy-preserving analytics, manufacturing systems.
Eligibility highlights: applicants must hold a Ph.D. by the effective date of appointment in Mechanical Engineering, Industrial & Systems Engineering, Electrical or Computer Engineering, or a closely related field. Required experience includes modeling/simulation of physical or manufacturing systems, machine learning or data-driven analysis, and peer-reviewed publications. Applicants must already be legally authorized to work in the United States and not require sponsorship.
Funding and benefits: the appointment is grant-funded; salary is based on qualifications, experience, internal equity, and departmental budget. WCU notes a benefits package that includes health, dental, and vision insurance, retirement contributions, and tuition waivers for eligible employees.
How to apply: submit the application online through the WCU jobs portal. Required materials include a cover letter, current CV, at least two publication samples, a research and scholarship statement, publication list, mentoring and student engagement statement, three references, and unofficial transcripts showing degree conferral dates. Review begins immediately and continues until the position is filled.
Funding details
Full-time, 12-month, time-limited, grant-funded postdoctoral appointment anticipated from about 2027-01-01 through 2029-06-30, with annual renewal contingent on satisfactory performance and continued funding. Salary is not specified in the post.
What's required
A Ph.D. by the effective date of appointment in Mechanical Engineering, Industrial & Systems Engineering, Electrical or Computer Engineering, or a closely related field is required. Candidates must already be legally authorized to work in the United States and not require immigration sponsorship. Applicants should have demonstrated research experience in modeling and simulation of physical or manufacturing systems, supporting experience in machine learning or data-driven analysis, and a record of peer-reviewed publications. Preferred experience includes validating simulation models against instrumented equipment or production data, edge computing platforms such as NVIDIA Jetson, embedded systems or real-time control, federated or distributed machine learning, privacy-preserving analytics, and deployment in operational or production settings.
How to apply
Apply online through the university job portal and submit the required materials: cover letter, CV, publication samples, research and scholarship statement, publication list, mentoring and student engagement statement, three references, and unofficial transcripts. Review begins immediately and continues until the position is filled.
More information can be found here
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