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    Researcher, Machine / Deep Learning and Cybersecurity working at NATIONAL UNIVERSITY SINGAPORE

    Job description

    We are looking for a Research Fellow who will be responsible for conducting in-depth research and innovation in implementing machine/deep learning (ML/DL) and association rule mining (ARM) that can applied to handle network security. The works must also lead to publication in leading international conferences and journals, as well as real-world implementation. Candidates must have the skills to implement and demonstrate Proof-of-Concept (PoC).

    Responsibility:

    • Develop adaptive strategies and algorithms using ARM and ML/DL models for automatic rule generation and mining on network traffic flow data;
    • ML/DL implementations can be enhanced with real-time/dynamic ARM techniques developed to classify traffic and reconfigure the network during attacks;
    • Develop application related use cases, deploy them as a proof of concept;
    • Towards patent filing
    • Must conduct performance evaluations/simulations for research works and must work towards publishing research articles;
    • Contribute to knowledge exchanges with external partners and collaborators;

    Degree

    • Doctoral Degree in Computer Science/Computer/Electrical Engineering, with machine-related expertise/experience/deep learning and cybersecurity;
    • Ability to conduct proven independent research with a strong and relevant publishing record;
    • Prior experience in network security and ML/DL, network traffic stream data processing, information extraction, real-time or dynamic Association Rule based strategies would be an asset;
    • Be prepared for network-based deployment
    • Excellent verbal presentation and interpersonal communication skills
    • Open for fixed term contract.

    Notice of Covid-19

    At NUS, the health and safety of our staff and students is one of our top priorities, and COVID vaccinations support our commitment to the safety of our communities. and make NUS as safe and user-friendly as possible. Many of our roles require a large amount of physical interaction with students/staff/public. Even for work roles that can be performed remotely, there will be circumstances where a presence on campus is required.

    Taking the health and well-being of our staff and students into consideration, and to better protect everyone on campus, applicants are encouraged to be fully vaccinated against COVID-19 to ensure successful employment. with NUS.

    More information

    Location: Kent Ridge Campus
    Organization: College of Design and Engineering
    Faculty: Electrical and Computer Engineering
    Employee Referrals Eligibility: No
    Job request ID: 15275

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