Research Assistant in Computer Science/Engineering

Singapore University of Technology and Design


Research Assistant

Apply now Job no: 494655
Work type: Contract, full-time
Location: Singapore
Categories: Bachelor Degree, Information Systems Technology & Design, Others


Data stream processing enables users to process infinite data streams in real-time. Nowadays, it is a buzzword that appears ubiquitously due to its many applications, including the Internet of Things and 5G. To cope with the increasing demand, many stream processing systems have emerged, such as Storm, Flink, and Spark-streaming.

The PI has been working on two key areas: 1) architecting novel stream processing systems and algorithms, and 2) designing novel stream processing applications (e.g., online machine learning, trajectory analytics).

We have one open Research Assistant (RA) position in the aforementioned areas. Graduates in Computer Science or Computer Engineering, well-equipped with the skill-set described below are encouraged to apply.


Strong programming skills in C/C++/Java/Python; good writing skills; (ideally) knowledge in database (or stream processing) systems and analytics (e.g., data mining, machine learning, temporal, trajectory).


The RA is expected to work closely with the PI on one concrete research topic for one year, and the goal is to publish one research paper out of it, this will enhance the RA's CV in applying for Ph.D. scholarships or research jobs afterwards.

Interested graduate may apply, with a copy of recent CV, by writing to:

Positions will remain open until filled.


[1] Zhang et al. Towards Concurrent Stateful Stream Processing on Multicore Processors, ICDE’20.
[2] Segarraet al. Using Trusted Execution Environments for Secure Stream Processing of Medical Data, Distributed Applications and Interoperable Systems, 2019.
[3] Burkhalter et al. TimeCrypt: Encrypted Data Stream Processing at Scale with Cryptographic Access Control, NSDI’20.
[4] Fedoryszak et al. Real-time Event Detection on Social Data Streams, KDD'19.
[5] Ang et al. TraV: An Interactive Exploration System for Massive Trajectory Data, IEEE BIGMM’19.

Applications close: 31 May 2021 Singapore Standard Time

In your application, please refer to


amsterdam uni

antwerp uni

cambridge uni

florida uni

hamburg uni

harvard uni

hiroshima uni

oslo uni

purdue uni

ryerson uni

shanghai jiao tong uni

stockholm uni