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Yaman Hamed

5 months ago

PhD Opportunity in Applied Science, Statistical Modelling, Machine Learning, and Physics-Informed AI at Universiti Teknologi PETRONAS Universiti Teknologi PETRONAS in Malaysia

Degree Level

PhD

Field of study

Computer Science

Funding

Full-time PhD in Applied Science with a monthly stipend of RM 3,000. Tuition fees are waived for TA work.

Deadline

Expired

Country flag

Country

Malaysia

University

Universiti Teknologi PETRONAS (UTP)

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Keywords

Computer Science
Machine Learning
Deep Learning
Mathematics
Python Programming
Predictive Analytics
Multi-task Learning
Applied Science
Statistics
Statistical Modelling
Physics

About this position

Universiti Teknologi PETRONAS (UTP) is advertising a PhD opportunity in Applied Science for candidates interested in statistical modelling, machine learning, predictive analytics, and physics-informed / hybrid AI modelling.

The research focus includes statistics and data analytics, time series modelling, multitask neural networks, and physics-informed neural networks (PINNs). This is a research-based, full-time PhD vacancy with an emphasis on advanced data-driven modelling for complex systems.

Funding: monthly stipend of RM 3,000 plus tuition fee waiver (for TA work).

Eligibility highlights: applicants must have a BSc in Statistics or Applied Mathematics, a minimum CGPA of 3.25 (or equivalent), and ISI-indexed Q1/Q2 journal publications. A strong quantitative background, solid programming skills (especially Python), and demonstrated research capability are required. Experience or strong interest in deep learning, time series modelling, and physics-informed modelling is preferred.

Application deadline: 31 May 2026.

How to apply: complete the PhD Candidate Screening Form at the provided link. Only shortlisted candidates will be contacted.

Funding details

Full-time PhD in Applied Science with a monthly stipend of RM 3,000. Tuition fees are waived for TA work.

What's required

Applicants must hold a BSc in Statistics or Applied Mathematics, with a minimum CGPA of 3.25 or equivalent. ISI-indexed Q1/Q2 journal publications are required. Candidates should have a strong foundation in statistics, mathematical modelling, and optimization, proficiency in Python programming, demonstrated research capability, analytical thinking, and the ability to work independently. Preference is given to applicants with experience or strong interest in deep learning, time series modelling, and physics-informed modelling, and priority may be given to Malaysian students or international students currently residing in Malaysia.

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Professors

Data Scientist - Researcher - Lecturer at Universiti Teknologi PETRONAS

University Name
Country flag

Malaysia

Research Interests

Business Analytics

Actuarial Science

Computer Science

Multi-task Learning

Desalination