PhD Scholarship (Industry) - Privacy-Preserving AI for Human-Centric Video Analytics

PhD Scholarship (Industry) - Privacy-Preserving AI for Human-Centric Video Analytics

Job No.: 696616

Location: Clayton campus

Employment Type: Full-time

Duration: The scholarship may be held for up to 3.5 years (full-time) for Research Doctorate (PhD) studies

Remuneration: The successful applicant will receive

• A Research Living Allowance, at current value of $37,145 AUD per annum for PhD (2026 rate with annual indexation)
• Faculty of Information Technology Tuition Fee Scholarship (for international students only)
• Industry Top-up scholarship of $10,000 per annum
• FIT Candidature Funding of $4,000 for the duration of the candidature
• Up to $1,265 from Monash Graduate Research Office as a one-off travel grant
• Top-up government scholarship $7,135 per annum

 The Opportunity

An exciting opportunity is available for an outstanding PhD candidate to undertake an Industry Linked PhD at Monash University in collaboration with Aervision Pty Ltd, an Australian AI company developing advanced video analytics solutions for critical infrastructure, public safety and smart environments. The successful candidate will be supervised by Dr Deval Mehta within the Department of Data Science & AI, Faculty of Information Technology, Monash University.

This project is funded through the Australian Government National Industry PhD Program and provides a unique opportunity to conduct cutting-edge AI research while working closely with industry to translate research into real-world products. The candidate will spend part of their candidature embedded within Aervision's research and development team, gaining hands-on experience in commercial AI development, product deployment and research translation.

To be considered for this opportunity you should fulfil the eligibility requirements listed below. The academic qualification requirements for this PhD is:

• A bachelor’s degree of at least four years in a relevant discipline, which includes a research thesis or project, with a minimum overall average grade of an honours degree equivalent to the First Class Honours; or
• A master's degree in a relevant discipline which includes a research thesis or project equivalent to at least 25 percent of one year of full-time study, with a minimum overall average grade of honours equivalent to the First Class Honours; or
• A qualification, or combination of qualifications and relevant professional experience, deemed equivalent by the GRC (or delegate).

Monash University strongly advocates diversity, equality, fairness and openness. We fully support the gender equity principles of the Athena SWAN Charter.

The Project

Modern video analytics systems must be accurate, privacy-preserving and capable of adapting to new environments without extensive retraining. Existing approaches often struggle with understanding complex human behaviour while satisfying privacy and real-time deployment requirements.

This PhD project aims to develop next-generation foundation models for privacy-preserving human-centric video analytics.

Research directions will include:

• Human action and activity recognition
• Individual and group behaviour understanding
• Long-term behaviour prediction
• Multi-task learning and foundation models
• Zero-shot and open-set recognition
• Privacy-preserving AI using anonymised human representations
• Efficient AI deployment on edge devices
• Real-world AI systems for security, healthcare and smart environments

The research will utilise anonymised industry datasets and be validated using Aervision's commercial AI platforms, providing a direct pathway from research to deployment. The project will contribute to Australia's capability in trustworthy and responsible AI while advancing commercially deployable video analytics technologies.

Candidate Profile

We are seeking highly motivated applicants with a strong academic background in computer science, data science and artificial intelligence. Applicants should ideally have experience in:

Essential

• Deep learning and machine learning
• Computer vision
• Python programming
• PyTorch or TensorFlow
• Strong mathematical and analytical skills

Desirable

• Video understanding
• Human action recognition
• Vision-language or foundation models
• Privacy-preserving AI
• Large-scale model training
• Publications in leading AI conferences or journals (CVPR, ICCV, AAAI, NeurIPS, and equivalent)

Excellent communication skills and enthusiasm for both academic research and industry collaboration are highly desirable.

Why Join This Project?

This scholarship provides:

• An Australian Government Industry PhD Scholarship
• Direct collaboration with an innovative Australian AI company
• Access to large-scale real-world industry datasets
• Industry placement throughout the PhD
• Access to Monash University's high-performance computing infrastructure
• Opportunities to publish in leading AI conferences and journals (CVPR, ICCV, AAAI, NeurIPS, and equivalent)
• Training in research commercialisation and technology translation
• Strong employment prospects in both academia and industry

This position has a two-stage selection process:

Stage 1: Please submit an EOI to

deval.mehta@monash.edu

With the EOI please include the documents - CV, academic transcripts and cover letter - and a draft research proposal of up to 5 pages, responding to your proposed plan for building Privacy-Preserving AI for Human-Centric Video Analytics.

The draft research proposal should demonstrate a clear description of the current problems in video analysis, a clear proposed framework to mitigate those issues, highlight the components of novelty and innovation in this domain. It should also outline your interest in being a PhD candidate at the Department of Data Science & AI and why this particular project interests you.

Stage 2: Candidates who pass this stage of the selection process will be invited to discuss their ideas with Dr Deval Mehta before developing and submitting a full application.

Enquiries: Dr Deval Mehta,

deval.mehta@monash.edu

Applications Close: Sunday 30 August 2026, 11:55pm AEST

We will begin the interview process as soon as suitable applications are received, so applicants are encouraged to apply early. We will not wait until the closing date to start shortlisting and interviews.

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