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  • Research Fellow (JOB-2019-0075884)
    School of Electrical and Electronic Engineering
    Nanyang Technological University

    ​The Delta-NTU Corporate Laboratory for Cyber-Physical Systems was jointly established by the School of Electrical and Electronic Engineering (EEE) at Nanyang Technological University (NTU) and Delta Electronics.

    The Corp Lab aims to create business value through collaborative commercialization of translational research and industrial development. Successful candidates will conduct research and development work related to Smart Manufacturing. The candidates are expected to contribute in effort targets pave new solution business in Smart Manufacturing in the Asia Pacific Region.

    Young and research-intensive, Nanyang Technological University (NTU Singapore) is ranked 13th globally. NTU is also placed 1st amongst the world's best young universities and ranked 4th globally for Engineering and Technology.

    Established in 1981, the SCHOOL OF ELECTRICAL AND ELECTRONIC ENGINEERING (EEE) is one of the founding Schools of the Nanyang Technological University. Built on a culture of excellence, the School is renowned for its high academic standards and research. With more than 150 faculty members and an enrolment of more than 4,000, of which about 1,000 are graduate students, it is one of the largest EEE schools in the world and ranks 6th in the field of Electrical & Electronic Engineering in the 2017 QS World University Rankings by Subjects.

    Delta Electronics was founded in 1971 and is a global leader in Power Electronics, Energy Management and Smart Green Life, with over 50 R&D sites globally and more than 5,000 R&D engineers.

    Job Description

    You will be responsible for developing natural language processing (NLP)/natural language understanding (NLU) technologies to support key application areas in the context of learning analytics. The overall scope of the project involves development of novel deep learning architectures for textual analysis obtained from in-house developed microphone system. As a research fellow, you will be responsible for the analysis of speech-to-text signals and text summarization.

    Job role:
    • Design and development of robust algorithms and techniques using text analytics, image analytics and machine learning
    • Integrate, simulate and test impact of algorithms and features on the overall system
    • Design and build machine learning and optimisation algorithms efficiently
    • Develop and execute necessary analyses, simulations or A/B tests to validate models and identify improvement opportunities
    • Results-oriented - ability to handle multiple, time-sensitive projects while focusing on the quality
    • Store, retrieve and visualise results in a manner that facilitates required analyses

    Job Requirements
    • PhD degree in Electrical/Electronics/Computer Engineering/Computer Science or relevant fields.
    • Knowledge of Machine Learning and Natural Language Processing theory and applications
    • Familiar with problems related to natural language understanding and machine translation and available Machine Learning/Deep Learning tools commonly used for implementation purposes
    • Comprehensive coding experience in at least one object oriented programming language (Java, C++, Python)
    • Strong development and engineering skills and experience with Deep Learning platforms (Tensorflow / Pytorch)
    • Excellent publication records in top-tier journals
    • Able to work independently and willing to co-operate with existing team members
    • Fluent in both verbal and written English;
    • Highly motivated and able to commit the whole period of the project

    Application Procedure:
    Interested candidates please send your CV/resume to:

    Assoc. Prof. Andy Khong
    School of Electrical & Electronic Engineering
    Nanyang Technological University
    50 Nanyang Avenue
    Block S2.1
    Singapore 639798

    E-mail Address for E-mailed Applications:
    Electronic submission of application is highly encouraged.

    Only shortlisted candidates will be notified for interview.

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