Developing AI-based wireless communication systems: dataset generation, deep learning model development, and optimization for intelligent precoding in multi-user visible light communication (VLC). This position is temporary, with an initial 3-month employment period.

• Develop and preprocess wireless communication dataset for multi-user VLC systems. 
• Implement and train deep learning models for intelligent precoding and wireless resource optimization. 
• Generate and analyze simulation data using wireless channel models and optimization-based solutions. 
• Evaluate model performance under different user configurations, channel conditions, and power constraints. 
• Conduct experiments, analyze results, and document findings to support research publications and ongoing project development.
   

• Strong programming skills in Python and experience with machine learning and deep learning frameworks such as TensorFlow or PyTorch. 
• Knowledge of wireless communications, machine learning, and optimization techniques. 
• Ability to analyze experimental results, troubleshoot models, and document technical findings.
• Bachelor's degree in Computer Science, Electrical Engineering, or a related field; Master's degree preferred.
   

Positions that are eligible for hybrid or mobile/remote work mode are at the discretion of the hiring department. Work agreements are reviewed annually at a minimum and are subject to change at any time, and for any reason, throughout the course of employment. Learn more about the work modes.

The University of Michigan conducts background checks on all job candidates upon acceptance of a contingent offer and may use a third party administrator to conduct background checks.  Background checks are performed in compliance with the Fair Credit Reporting Act.

The University of Michigan is an Equal Opportunity Employer. We are committed to providing an environment of mutual respect where equal employment opportunities are available to all applicants, including protected veterans and individuals with disabilities.