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 strong tradition in research. To support teaching and cutting-edge research, EEE is host to 11 research centres and more than 50 laboratories, which are well-equipped with modern facilities and state-of-the-art equipment. With about 200 faculty members and an enrolment of more than 4,000, of which about 1,300 are graduate students, it is one of the largest EEE schools in the world.
We are looking to hire a motivated post-doc to work on signal processing methods, machine learning, and data analytics in networks. The candidate must have a strong background in signal processing, optimization methods, probability, statistics, and/or machine learning methods.
- Develop algorithms for inference in multi-agent networks including sensor and/or social networks. Develop theories to quantify the fundamental performance limits of these estimators.
- Develop theories and algorithms for machine learning and data analytics. We will have access to different sensory data collected from a large-scale test-bed being built at NTU.
- Develop simulation platform and perform simulation studies.
- May be required to implement and perform empirical experiments to verify algorithm performance.
- Help to supervise graduate students and contribute to proposal writing.
- Ph.D. in Electrical Engineering, Computer Science, Statistics or other related fields.
- Solid Mathematical skills.
- Experience in machine learning and data analytics will be considered an asset.
- Bilingual and good in writing skills
Interested candidates please send your CV/resume to:
Prof Tay Wee Peng
School of Electrical & Electronic Engineering
Nanyang Technological University
50 Nanyang Avenue
E-mail Address for E-mailed Applications: firstname.lastname@example.org
Electronic submission of application is highly encouraged.
Only shortlisted candidates will be notified for interview.