Postdoc Research Scholar - Federated Learning, Embedded Systems, and Manufacturing - #270026

Western Carolina University; Cullowhee (NC); On-site; USD 58,000 - 72,000; Full time

Job summary

Western Carolina University seeks a Postdoc Research Scholar to advance federated learning, embedded AI, and manufacturing data streams. Work on-device inference, edge platforms, and secure communications, deploying at partner sites in NC.

You will mentor students, publish results, and contribute to collaborative research with NC State University, reporting to the principal investigator. On-site in Cullowhee; travel to NC partner sites required.

Qualifications

• Ph.D. in EE/CE/Mech or related field by start date
• Experience with federated learning and deploying ML on resource-constrained embedded systems
• Strong Linux, Git, and networking knowledge

Responsibilities

• Conduct postdoctoral research on federated learning for embedded AI in manufacturing
• Design and implement ML models for on-device inference on embedded/edge hardware
• Develop and evaluate use-case models (defect detection, energy forecasting, robot control)
• Collaborate with university and industry partners; mentor students and contribute to proposals

Skills

Federated learning

Privacy-preserving techniques

Embedded/edge ML deployment

Linux OS

Git/GitHub

C/C++ for embedded

Machine vision

Mentoring students

Education

Ph.D. in Electrical Engineering, Computer Engineering, Mechanical Engineering, or related field

Tools

PyTorch

TensorFlow

Jetson Nano

GCC/C/C++ toolchain

Git/GitHub

Job description

Postdoc Research Scholar – Federated Learning, Embedded Systems, and Manufacturing #270026

Position Summary

The primary location of this position is on-site in Cullowhee, NC. Those serving in this position should expect periodic travel to partner manufacturing sites in North Carolina. Remote work is not available.

This is a full-time, 12-month, time-limited, grant-funded appointment anticipated to begin as soon as early November 2026, and continue through June 30, 2027, with annual renewal contingent on satisfactory performance and continued funding.

The primary purpose of this position is to conduct postdoctoral research supporting the embedded AI systems and manufacturing data streams of a Federated Learning Framework for Advanced Manufacturing Environments. The position designs and implements federated learning models to be deployed at the machine nodes using embedded systems platforms; networks the nodes with the federated learning servers, deploys and manages the federated learning servers; develops and evaluates use-case models such as defect detection, energy and demand forecasting, and adaptive machine and robotic control; selects and integrates embedded and edge computing platforms for on-device inference; designs the communication layer for real manufacturing network constraints; and supports evaluation and deployment of the framework at industry partner sites.

The position also contributes to scholarly publications, project deliverables, student mentoring, curriculum modules, and hands-on training activities as a member of a joint Western Carolina University and North Carolina State University research team. The position reports to the project principal investigator.

Required Knowledge, Skills, and Abilities

• Strong experience using Federated learning open source or commercial frameworks.
• Strong experience with privacy-preserving and secure aggregation techniques.
• Strong ability to develop, deploy, and profile machine learning models on resource-constrained embedded and edge hardware using PyTorch or TensorFlow, and C/C++ for embedded development.
• Mastery of the Linux OS and networking stack, and Git/GitHub for code management.
• Experience in data acquisition from CNC controllers, PLCs, or industrial robot controllers; familiarity with Haas or FANUC control interfaces is a particular asset.
• Experience in Embedded/Edge Platforms like Jetson Nano and the associated system interfaces and interface protocols, as well as optimization toolchain for embedded inference.
• Experience in Machine vision for defect detection, time-series forecasting, or reinforcement learning for machine control.
• Experience mentoring students and contributing to funded research proposals.

Minimum Qualifications

A Ph.D. (by the effective date of appointment) in Electrical Engineering, Computer Engineering, Mechanical Engineering, or a closely related field, with demonstrated research experience in federated or distributed machine learning and in deploying machine learning models on resource-constrained embedded and edge platforms; working knowledge of networking and data security; and a record of peer-reviewed publications in highly ranked venues.

Preferred Qualifications

• Advanced knowledge of federated or distributed machine learning, including framework architecture, aggregation methods, and personalization strategies that address non-IID data arising from differences in machines, sensors, and operating conditions.
• Ability to deploy and manage machine learning models on-prem and cloud computational resources.
• AIOps/MLOps: applying artificial intelligence and machine learning pipelines to automate operations, monitor performance, and manage model deployments.
• Knowledge of industrial communication protocols such as MTConnect, OPC UA, Modbus TCP, EtherNet/IP, PROFINET, or MQTT, and of TCP/IP networking including multicast, as applied to networked cyber-physical or industrial IoT systems in manufacturing environments such as CNC machining, industrial robotics, or additive manufacturing.
• Ability to plan, conduct, document, and communicate independent and collaborative research through technical reports, project deliverables, peer-reviewed manuscripts, presentations, and partner-facing discussions.
• Ability to work effectively with faculty, student researchers, university collaborators, and industry partners; safely operate around production manufacturing equipment; and travel periodically to partner sites within North Carolina.

Position Type

• Position Type: Time-Limited Full-Time
• Number of Hours Per Week: 40
• Number of Months Per Year: 12

About Western Carolina University

• 2025 - Ranked 1st in the top 100 employers in North Carolina in Forbes 'America's Best Employers by State' list.
• 2024 - Ranking in the top 8.5% on Forbes 'America's Best Midsize Employers' list, WCU was ranked 34 out of the top 400 employers across all industries.
• 2023 - Ranked in the top 20% on Forbes 'America's Best Midsize Employers' list, WCU was ranked 97 out of the top 500 employers across all industries.
• 2022 - Ranked 14th in the top 100 employers in North Carolina in Forbes 'America's Best Employers by State' list.

Western Carolina University is the UNC system’s westernmost campus and has been consistently ranked as one of the top 15 public regional institutions in the South.

• Employees of WCU are provided a comprehensive benefits package as well as other resources, policies and programs to ensure a happy and healthy work/life balance.
• Benefit eligible employees have access to dental, vision and health insurance plans – eligibility begins on the first of the month following date of hire.
• Retirement plan contributions begin on the eligibility date following election and include employer contributions for either a defined contribution or a defined benefit plan.
• Optional disability plans are also available.
• Eligible employees have access to tuition waivers for up to three courses per academic year; employee may enroll at any of the constituent UNC System campuses.
• Also offered are free group exercise classes multiple times per week, a discounted membership to the campus recreation center, free vaccine and booster shots offered on campus, pretax flexible spending accounts, 12 paid holidays and 24 hours of paid community service leave each year.
• Leave earning employees (staff and 12-month faculty) who work at least half of the working days of their first month of employment will begin accruing vacation and sick leave immediately.
• Paid parental leave after 12 months of continuous service.
• WCU offers an abundance of training and development programs, certifications, workshops and conferences - many of which are offered free of charge.

Background/E-Verify

Final candidates are subject to criminal & sex offender background checks. Some vacancies also require credit or motor vehicle checks.

Western Carolina University uses E-Verify to confirm employment eligibility of all newly hired employees. To learn more about E-Verify, including your rights and responsibilities, please visit www.dhs.gov/E-Verify. Proper documentation of identity and employability are required at the time of employment.

Credential Verification

All new employees are required to have listed credentials/degrees verified within 30 days of employment. All new employees who will be teaching are required to provide official transcripts within 30 days of employment. Transcripts should be provided for the highest earned degree and/or the degree which is being used to satisfy credential/qualification requirements.

Equal Opportunity Employer

Western Carolina University is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race; color; ethnicity; religion; sex; pregnancy; sexual orientation; gender identity or expression; national origin; age; disability; genetic information; political affiliation; National Guard or veteran status, consistent with applicable federal, state and local laws, regulations, and policies, and the policies of The University of North Carolina. Persons with disabilities requiring accommodations in the application and interview process please call [phone] or email at [e-mail].

University Safety

The Western Carolina University Annual Safety Report is available online at University Annual Safety Report or in hard-copy by request at the office of the Vice Chancellor for Student Affairs, 227 HFR Administration Building, Cullowhee, NC 28723 (828-227-7147) or the Office of University Police, 111 Camp Annex, Cullowhee, NC 28723 (828-227-7301). The report, required of all universities participating in Title IV student financial aid programs, discusses crime statistics, procedures for reporting suspicious or criminal activity, security, police authority, crime prevention strategies, university policies on substance abuse and sexual offenses, workplace violence and fire safety.