Education H-1B Sponsorship Jobs in North Carolina

INTRODUCTION

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.

BASIC QUALIFICATIONS

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.

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

Time-Limited Full-Time

NUMBER OF HOURS PER WEEK

40

NUMBER OF MONTHS PER YEAR

12

POSTING TEXT

Open Date 10/28/2026

Close Date

Open Until Filled Yes

SPECIAL INSTRUCTIONS TO APPLICANTS

Application materials must be submitted online. Review of applications will begin immediately and will continue until a candidate has been selected for hire. Please include the following:
- letter of application (cover letter)
- current CV
- samples of at least two transactions or journal publications at high impact factors venues.
- statement of research and scholarship goals (no more than two pages)
- list of publications
- statement of mentoring and student engagement goals
- list of three professional references with complete contact information
- unofficial transcripts showing degree conferral dates for all degrees at the master’s degree level and higher*

For questions or additional information please contact Dr. Islam Elgarhy at ielgarhy@wcu.edu

• All applicants are required to submit an unofficial transcript of their highest attained degree, showing all completed coursework and the date the degree was conferred. The transcript must state Degree Awarded, Degree Conferred, or a similar phrase. For candidates who are ABD, please submit your most recent doctoral program transcript along with your master’s degree transcript, if you hold such a degree. The master’s degree transcript must have a notation such as Degree Awarded, Degree Conferred, or a similar phrase, to verify it as your highest completed degree.

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.

EOE

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 (828) 227-7218 or email at jobs@email.wcu.edu.

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.