Research Fellow , Machine/Deep Learning and Network Security

30 Sep 2022
End of advertisement period
30 Oct 2022
Contract Type
Fixed Term
Full Time

Job Description

We are looking for a Research Fellow who will be responsible for undertaking in-depth research and innovation in machine/deep learning (ML/DL) and association rule mining (ARM) implementations that can be applied to handle network security. The works must also lead to publications in top-tier international conferences and journals, as well as real-world implementations. Candidate must be skilled to implement and demonstrate a Proof-of-Concept (PoC).


  • Develop algorithms and adaptive strategies using ARM and ML/DL models for automatic rule generation and mining on network traffic flow data;
  • Implement ML/DL that may be augmented with real-time/dynamic ARM techniques developed to classify the traffic and to reconfigure the network during attacks;
  • Develop use cases relevant to the application, implement them as a proof-of-concept;
  • Work towards filing an invention disclosure
  • Must conduct performance evaluations/simulations for research works and must work towards publishing research articles;
  • Contribute to knowledge exchange activities with external partners and collaborators;


  • A PhD in Computer Science/Computer/Electrical Engineering, with specialization/experience related to machine/deep learning and network security;
  • Proven ability to conduct independent research with a strong and relevant publication record;
  • Prior experience in network security and ML/DL, network traffic flow data handling, information extraction, dynamic or real-time Association Rule Mining based strategies will be an asset;
  • Must be prepared to do network-based implementations
  • Excellent interpersonal communication and oral presentation skills 
  • Open to fixed term contract.

Covid-19 Message

At NUS, the health and safety of our staff and students are one of our utmost priorities, and COVID-vaccination supports our commitment to ensure the safety of our community and to make NUS as safe and welcoming as possible. Many of our roles require a significant amount of physical interactions with students/staff/public members. Even for job roles that may be performed remotely, there will be instances where on-campus presence is required.

Taking into consideration the health and well-being of our staff and students and to better protect everyone in the campus, applicants are strongly encouraged to have themselves fully COVID-19 vaccinated to secure successful employment with NUS.

More Information

Location: Kent Ridge Campus
Organization: College of Design and Engineering
Department : Electrical and Computer Engineering
Employee Referral Eligible: No
Job requisition ID : 15275

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