Job Description

One of the main objectives of Federated Learning (FL) is to protect the privacy of participants, i.e., the participants only need to share parameters of the trained model instead of sharing their actual data. However, some recent research works have shown that privacy and security concerns may arise when the FL participants or FL servers are malicious in nature. In particular, this defeats the purpose of FL since the resulting global model can be corrupted, or the participants may even have their privacy compromised during model training. In this research project, secure and privacy-preserving federated learning in the edge computing paradigm specifically in health-care and autonomous systems will be analyzed and implemented considering the system performance.

Responsibilities and Duties

The successful candidates will be selected based on their research ability, prior expertise in reverse engineering tasks, and strong technical knowledge in deep learning models.

• Analyzing the privacy and security challenges in the federated learning in edge computing such as in the health-care and autonomous systems
• Analyzing the required tools and frameworks to implement the federated learning for edge computing paradigm
• Implementing the secure and privacy-preserving federated learning for edge computing Paradigm Interested candidate can send their resumes to: serhanim@uaeu.ac.ae, including a cover letter, and a brief statement of your work undertaken in previously. The employment period is six months up for renewal based on evaluation of performance.

Minimum Qualification

• Master degree

Preferred Qualification

Necessary requirements for the research assistant include research focus on machine learning, applied mathematics, IoT, edge computing, and interference management and optimization. Good written and oral communication skills in English are essential. Salary is provided based on qualification.

Expected Skills/Rank/Experience  

Special Instructions to Applicant  

Division College of Information Tech. -(CIT)
Department As.Dean for Research&Grad.Std.- CIT
Job Close Date 31-03-2021
Job Category Academic - Research Assistant