Postdoc Position - CPS Modelling for Smart Manufacturing (NTU, Singapore)

We are seeking a strong and motivated candidate for the position of Research Fellow (Postdoctoral Fellow) in the area of Cyber-Physical Systems, with research focus on the modelling, simulation and synthesis of continuous time and discrete time models. This work will enable the development of a cyber-twin, which represents various processes of a factory in a smart manufacturing environment. This position is part of a corporate lab initiative involving NTU and Delta Electronics, a leading electronics manufacturing company. The expected start date for the position is July 2017, and the expected duration of the position is 2.5 years. Remuneration will be attractive and commensurate based on the qualifications and suitability for the project.

The candidate is expected to have a PhD degree in Computer Sciences, Computer Engineering, Electrical Engineering or related fields. The candidate must demonstrate a strong research experience in one or more of the following areas:

1. Modelling and simulating hybrid systems based on mathematical models such as Hybrid Automata, ODEs, Timed Automata, MATLAB Simulink/Stateflow etc.

2. Background in developing formal semantics to capture interactions between models in a complex CPS.

3. Understanding the nuances in discretising continuous timed models, e.g., zero-crossing error after discretising hybrid automata into a finite-state machine.

4. Experience in translating mathematical models to C-code while preserving semantics is desired.

Experience in both design as well as implementation of technologies for CPS is highly desirable. The candidate will be responsible for the management of the overall project, and will lead a team of 2 Research Assistants and 1 PhD student. The position is expected to provide an excellent opportunity to perform both fundamental as well as translational research in close collaboration with industry.

Salary Range: SGD4000-SGD6000 per month.

Project Overview: With sensing technology becoming pervasive in manufacturing plants, large amounts of data are being generated in real-time. As a consequence, there is a fundamental need to effectively utilize this "big data" so that many of the desired objectives of Industry 4.0 such as predictive maintenance, agile manufacturing and re-configurability, can be realized. The concept of a cyber twin to transform big data into meaningful information about the plant has a wide range of applications. The cyber twin can be viewed as an accurate and time-synchronized characterization of the physical plant in the cyber domain.

In this project, we propose to develop a model-based design and deployment framework to realize the concept of a cyber twin. Model-based design enables the use of correct-by-construction methodology to generate code for both the physical plant controllers as well as the cyber twin, thus ensuring the accuracy of the twin as well as its compatibility with plant controllers. Motivated by the idea of synchrony hypothesis, the project aims to develop a tool suite with the following objectives: 1) Plant and controller model specification and simulation to characterize the cyber twin, and 2) Automatic model-to-code transformation for controller and cyber twin synthesis.

How to Apply: Send an email with CV to Arvind Easwaran (arvinde@ntu.edu.sg)