Numerical and AI Modelling of Screening, Briquetting and Agglomeration PhD Scholarship – Eligibility, Benefits & How to Apply

🌟 About the Scholarship

Opens
Closes31 Aug, 2026

The Numerical and AI Modelling of Screening, Briquetting and Agglomeration PhD Scholarship is a fully funded doctoral research scholarship offered by the School of Engineering at Western Sydney University, Australia. The scholarship provides comprehensive financial support throughout the doctoral program. It includes a tax-free annual living stipend, tuition support through the Australian Government Research Training Program (RTP), and funding for approved research activities, conference participation, and industry engagement. In addition, scholars gain access to advanced computational facilities, modern engineering laboratories, and expert academic supervision at Western Sydney University. They also collaborate with industry partners on real-world engineering projects that strengthen both technical expertise and professional experience. Consequently, recipients develop valuable research skills while building strong academic and industry networks.

🎓 Scholarship Snapshot

Here’s everything you need at a glance: the documents to prepare, what the award covers, and key dates so you don’t miss a beat. From transcripts and essays to tuition and living support, this gives you a clear picture of the Numerical and AI Modelling of Screening, Briquetting and Agglomeration PhD Scholarship before you apply.

Eligible Countries

Afghanistan, Albania, Algeria, Andorra, Angola, Antigua and Barbuda, Argentina, Armenia, Aruba, Australia, Austria, Azerbaijan, Bahamas, Bahrain, Bangladesh, Barbados, Belarus, Belgium, Benin, Bhutan, Bolivia, Bosnia-Herzegovina, Botswana, Brazil, Brunei Darussalam, Bulgaria, Burkina Faso, Burundi, Cabo Verde, Cambodia, Cameroon, Canada, Cape Verde, Central African Republic, Chad, Chile, China, Colombia, Comoros, Costa Rica, Côte d’Ivoire, Croatia, Cuba, Cyprus, Czech Republic, Democratic Republic of the Congo, Denmark, Djibouti, Dominica, Dominican Republic, East Timor, Ecuador, Egypt, El Salvador, Equatorial Guinea, Eritrea, Estonia, Eswatini, Ethiopia, Fiji, Finland, France, Gabon, Gambia, Georgia, Germany, Ghana, Greece, Greenland, Grenada, Guam, Guatemala, Guinea, Guinea Bissau, Guyana, Haiti, Honduras, Hong Kong, Hungary, Iceland, India, Indonesia, Iran, Iraq, Ireland, Israel, Italy, Jamaica, Japan, Jordan, Kazakhstan, Kenya, Kiribati, Kosovo, Kuwait, Kyrgyzstan, Lao People’s Democratic Republic, Laos, Latvia, Lebanon, Lesotho, Liberia, Libya, Liechtenstein, Lithuania, Luxembourg, Madagascar, Malawi, Malaysia, Maldives, Mali, Malta, Marshall Islands, Mauritania, Mauritius, Mexico, Micronesia, Moldova, Monaco, Mongolia, Montenegro, Morocco, Mozambique, Myanmar, Namibia, Nauru, Nepal, Netherlands, New Zealand, Nicaragua, Niger, Nigeria, Niue, North Korea, North Macedonia, Norway, Oman, Pakistan, Palau, Palestine, Panama, Papua New Guinea, Paraguay, Peru, Philippines, Poland, Portugal, Puerto Rico, Qatar, Romania, Russia, Rwanda, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, Samoa, San Marino, Sao Tome and Principe, Saudi Arabia, Scotland, Seirra Leone, Senegal, Serbia, Seychelles, Sierra Leone, Singapore, Slovakia, Slovenia, Solomon Islands, Somalia, South Korea, South Sudan, South-Africa, Spain, Sri Lanka, Sudan, Suriname, Swaziland, Sweden, Switzerland, Syrian Arab Republic, Taiwan, Tajikistan, Tanzania, Thailand, Timor-Leste, Togo, Tokelau, Trinidad-Tobago, Tunisia, Turkey, Tuvalu, Uganda, Ukraine, United Arab Emirates, United Kingdom, United States, Uruguay, Uzbekistan, Vanuatu, Vatican City, Venezuela, Vietnam, Wales, Yemen, Zambia, Zimbabwe

Study Fields

Engineering

GPA / Grade

GPA 3.0

Languages

IELTS 6.5, PTE A 58, TOEFL iBT 82

Tests

Study Levels

Doctoral, PhD

Total Scholarships

Transcripts

Yes

Degrees

Yes

Essay

Yes

Passport ID

Recommendation Letters

Yes (1)

Result Date

Program Start

2027

Tuition Fee

Covered

Living Allowance

Yes

AUD 35,188/year

Travel Allowance

Research Grant

Health Insurance

Visa Assistance

📞 Contact Information

Call if you want a quick answer, send an email for detailed questions, or follow the university’s social channels to keep an eye on updates and reminders. Use whatever fits your style and timezone.

Scholarship Summary

Award AmountAUD 35,188/year
Deadline31 Aug, 2026
LevelDoctoral, PhD
InstitutionWestern Sydney University
CountryAustralia
ModeOnline
TypeFully funded

Apply Now

The Numerical and AI Modelling of Screening, Briquetting and Agglomeration PhD Scholarship is a fully funded doctoral research scholarship offered by the School of Engineering at Western Sydney University, Australia. The project is supported through an Australian Research Council (ARC) Linkage Project in partnership with industry. It focuses on developing advanced numerical and artificial intelligence (AI) models to improve mineral processing technologies. Moreover, the research addresses critical challenges in screening, briquetting, and agglomeration processes that play an essential role in material handling, resource recovery, and sustainable mineral production. Through this scholarship, doctoral researchers contribute to the digital transformation of the mining industry while developing expertise in AI-driven engineering solutions.

Background and Purpose

The scholarship aims to improve the efficiency, sustainability, and automation of mineral processing operations through advanced computational modelling and artificial intelligence. The research investigates particle behavior during screening, briquetting, and agglomeration by integrating machine learning, discrete element modelling (DEM), numerical simulation, and process modelling. Furthermore, the project develops predictive AI-based models that optimize industrial processes, improve product quality, reduce energy consumption, and enhance operational performance. It also supports the mining industry’s transition toward intelligent and environmentally sustainable processing technologies. As a result, the research contributes to Australia’s growing focus on digital innovation and sustainable resource development.

Numerical and AI Modelling of Screening, Briquetting and Agglomeration PhD Scholarship Benefits

The scholarship provides comprehensive financial support throughout the doctoral program. It includes a tax-free annual living stipend, tuition support through the Australian Government Research Training Program (RTP), and funding for approved research activities, conference participation, and industry engagement. In addition, scholars gain access to advanced computational facilities, modern engineering laboratories, and expert academic supervision at Western Sydney University. They also collaborate with industry partners on real-world engineering projects that strengthen both technical expertise and professional experience. Consequently, recipients develop valuable research skills while building strong academic and industry networks.

Eligibility Criteria

Applicants must satisfy the admission requirements for a PhD program at Western Sydney University. Additionally, they should possess an excellent academic record and hold qualifications in mechanical engineering, mining engineering, mineral processing, chemical engineering, materials engineering, computer science, artificial intelligence, data science, or a closely related discipline. Candidates with experience in computational modelling, machine learning, discrete element modelling, programming, particle technology, or process simulation may receive preference. Furthermore, applicants should demonstrate strong analytical ability, research potential, and an interest in interdisciplinary engineering research.

Numerical and AI Modelling of Screening, Briquetting and Agglomeration PhD Scholarship Application Process

Eligible applicants must apply for admission to the PhD program at Western Sydney University and submit all required scholarship application documents. The selection committee evaluates candidates based on their academic achievements, research experience, technical expertise, programming skills, and suitability for the project. Shortlisted applicants may also participate in interviews before the university makes the final selection. Successful candidates will undertake the research in collaboration with experienced researchers and industry partners through the ARC Linkage Project.

Opportunities for Scholars

The scholarship provides exceptional opportunities to conduct industry-focused research that combines artificial intelligence, computational modelling, and mineral processing engineering. As a result, scholars gain advanced expertise in machine learning, numerical simulation, discrete element modelling, process optimization, programming, data analytics, and scientific research. Furthermore, they collaborate directly with industry partners to develop innovative AI-driven solutions for sustainable mineral processing and automated industrial systems. Their research also contributes to improving resource efficiency, reducing environmental impacts, and advancing digital technologies within the mining sector. Ultimately, the scholarship prepares graduates for successful careers in mining engineering, mineral processing, artificial intelligence, advanced manufacturing, process engineering, research organizations, and academia.

Frequently Asked Questions (FAQs)

Who is eligible?

Applicants must meet Western Sydney University’s PhD admission requirements and hold a First Class Honors degree, a research master’s degree, or an equivalent qualification. A background in mining engineering, mineral processing, mechanical engineering, chemical engineering, computational modelling, artificial intelligence, or a related field is preferred.

How do I apply?

Applicants should submit an Expression of Interest (EOI) to the project supervisor before lodging a formal PhD application through Western Sydney University. The EOI should be submitted at least five business days before the application deadline.

What is the focus of the research project?

The project develops numerical simulation and artificial intelligence models to optimize screening, briquetting, and agglomeration processes for mineral processing, improving efficiency, productivity, and sustainability in the resources sector.