Master of Philosophy (Chemical Engineering)

Vacant MPhil position

The research project “Development of a Rapid and Cost-Effective Detector and Estimator of Adulterants in Ground Sarawak Black Pepper using Spatial and Spectral Image Analysis” offers a fully funded two year Master research position. This project is a multidisciplinary research combining applied chemistry and computer sciences especially related to artificial intelligence. The position will be filled as soon as possible with a starting date no later than 1st January 2019.

 

ELIGIBILITY

To be eligible, a candidate should have:

  1. A Malaysian
  2. Willingness to learn new things and to conduct breakthrough research.
  3. A Bachelor degree graduated with, or qualified for, the award of the degree of Bachelor with First Class Honours or Second Class Honours or CGPA 2.67 in one of these disciplines: Chemical Engineering, Applied Chemistry and Electrical Engineering.
  4. Good command of written and spoken English (e.g. IELTS: overall band of 6.5 and no individual band below 6.0).

  

FUNDING NOTE

This research is a part of the project funded by Sarawak Multimedia Authority through Digital Sarawak Centre of Excellence 2018 – 2020. The PhD scholarship will cover full tuition-fee and annual stipend of MYR 24,000. The duration of this scholarship is two years.

 

MPhil SUPERVISION AND PROJECT TEAM

The MPhil project will be supervised by Dr. Agus Saptoro, Dr. Garenth Lim King Hann and Dr. Chua Han Bing. The successful applicant may also work in tandem with the teams from Malaysian Pepper Board (MPB) and Universiti Malaysia Sarawak (UNIMAS).

  

PROJECT DESCRIPTION

Malaysia is the world’s sixth largest pepper producer and more than 95% Malaysian-grown pepper come from Sarawak.  Therefore, for Sarawak, pepper, especially black pepper, is an important agricultural commodity contributing to the state’s economy. Consequently, efforts have been directed toward maintaining and/or improving the quality of Sarawak black pepper either in whole pepper or ground pepper. In the market, however, adulterated black pepper products exist in which black pepper is contaminated with different types of adulterants. Quality monitoring in detecting these adulterants is usually carried out using either physical (density difference) method or analytical method. The first method is fast, simple and practical however, quantitative information is unavailable. Meanwhile, the later one is associated with cost-ineffective and time-consuming and requires sophisticated analytical instrumentations and expertise. This project, therefore, aims to develop a rapid, reliable and cost-effective detector and estimator of adulterants in black pepper powder. The backbone of this proposed technology will be deep learning artificial neural networks (DLANN) based image processing, classifier and predictor. Spatial and spectral images and chemical/biochemical, microbiological and physical data of ground black pepper will be collected and used to build and validate DLANN models. Then, these models will be implemented as faster and cheaper adulterant detection and estimation systems of ground black pepper compared to the traditional laboratory analyses. These project outputs are envisaged to directly benefit Sarawak black pepper industry players and regulators in monitoring the product quality and support the efforts in maintaining the reputation of Sarawak black pepper in both domestic and international markets to indirectly contribute to Sarawak digital economy.

 

INTERESTED TO APPLY?

Potential candidates should contact:

 

Associate Professor Dr. Agus Saptoro
Department of Chemical Engineering | Faculty of Engineering and Science
Curtin University, Malaysia

Tel | +60 85 443 939 Ext. 2539 (GMT +8)
Fax | +60 85 443 838
Email | agus.saptoro@curtin.edu.my
Web | www.curtin.edu.my

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