University Malaysia Pahang Al-Sultan Abdullah
6 days ago
PhD Opportunity in Deep Learning and Acoustic Leak Detection at Universiti Malaysia Pahang Al-Sultan Abdullah Universiti Malaysia Pahang Al-Sultan Abdullah in Malaysia
Degree Level
PhD
Field of study
Computer Science
Funding
Full funding availableCountry
Malaysia
University
University Malaysia Pahang Al-Sultan Abdullah

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About this position
PhD opportunity at Universiti Malaysia Pahang Al-Sultan Abdullah (UMPSA) in the Faculty of Mechanical and Automotive Engineering Technology for a project on deep learning and acoustic leak detection. The research topic is “Formulation of a Deep Learning Model for Acoustic-Based Leak Detection in Water Pipelines under Varied Operational Conditions.”
This opening is well suited to candidates interested in mechanical engineering, machine learning, signal processing, and water pipeline monitoring. The project focuses on developing an AI-based model for detecting leaks using acoustic data under different operating conditions, with opportunities to work on funded research, publish in WOS-indexed journals, and build an academic profile.
Funding: Monthly stipend of RM2,800 for up to 3 years. Additional support includes academic mentorship, conference participation, networking, exposure to grant-funded projects, and publication support.
Eligibility: Open to both local and international applicants. Applicants should hold a Master’s degree or a First Class Bachelor’s degree in Engineering or a related field (or equivalent). Proficiency in MATLAB or Python is an advantage, and prior experience writing for WOS-indexed journals is also preferred.
How to apply: Email your CV and academic transcripts directly to Professor Ir. Dr. Mohd Fairusham bin Ghazali at [email protected].
Funding details
Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.
How to apply
Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.
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