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Industrial and Systems Engineering● OpenMastersPreview

Master of Engineering Practice in Intelligent Industrial Control and Autonomous Systems

A hands-on master’s programme blending AI, robotics, and industrial automation for careers in smart manufacturing and autonomous systems.

Best for:Best for engineers with a four-year accredited degree in engineering or related fields, seeking to specialise in AI-driven industrial control, robotics, and autonomous systems for smart manufacturing careers.

Murdoch University · Perth, Australia
More professors at Murdoch University
Industrial Internet of Things (IIoT)Machine Learning in Industrial AutomationMobile Robotics and Autonomous SystemsData Analytics for Smart ManufacturingControl Systems EngineeringAI-Driven Process Optimization
This is a masters position — not a PhD studentship.
Deadline
—
Funding
—
Start date
flexible (depends on intake)
Full-time
Location
Perth
Australia

Overview

This Master of Engineering Practice specialisation at Murdoch University equips graduates with practical expertise in designing, prototyping, and controlling modern industrial and autonomous systems. Students explore data analytics, machine learning, the Industrial Internet of Things (IIoT), and mobile robotics, preparing them for diverse roles across manufacturing, logistics, and automation sectors. The curriculum emphasises real-world applications, ensuring graduates can address challenges in smart factories and autonomous technologies. Ideal for engineers seeking to specialise in cutting-edge control systems and AI-driven industrial solutions, the programme balances theoretical knowledge with hands-on experience. Admission pathways accommodate diverse backgrounds, including engineering degrees, relevant industrial experience, or prior studies in engineering technology.

Industrial AutomationSmart ManufacturingRobotics EngineeringAI in ManufacturingControl SystemsEngineering PracticeAutonomous SystemsData-Driven Engineering

What you'll do

  • Design and prototype modern industrial and autonomous systems using advanced engineering principles and AI technologies.
  • Apply data analytics and machine learning techniques to optimise industrial processes and control systems.
  • Develop solutions for smart manufacturing environments, including IIoT integration and mobile robotics.
  • Collaborate on interdisciplinary projects to address real-world challenges in automation and control systems.
  • Gain hands-on experience through practical coursework and industry-relevant case studies.
  • Contribute to research and innovation in intelligent industrial systems, bridging theory and application.

Requirements

Degree required: One of the following: (1) A four-year Engineering degree accredited by Engineers Australia or an equivalent Washington Accord-recognised degree in an approved engineering field; (2) A Bachelor’s degree (AQF Level 7) with prior studies in Engineering or Engineering Technology; (3) A Bachelor’s degree (AQF Level 7) in a cognate area with appropriate industrial experience; (4) Domestic applicants with industrial experience may be admitted with additional specified units to meet knowledge requirements.

Degree offered: Master of Engineering Practice

Language: English proficiency (if applicable, though not explicitly stated in the source data)

Instruction: English

Required skills
  • Proven problem-solving and analytical skills in engineering contexts
  • Basic understanding of engineering principles and practices
  • Ability to work collaboratively in interdisciplinary teams
  • Familiarity with data analytics and computational tools (e.g., programming, simulation software)
Nice to have
Experience with machine learning or AI toolsPrior exposure to industrial automation or roboticsKnowledge of control systems or IoT technologies
Eligibility
  • Applicants must meet one of the four specified admission pathways (degree, industrial experience, or advanced standing).
  • Domestic applicants with industrial experience may be admitted conditionally with additional coursework.
  • Advanced standing for prior studies will be considered on a case-by-case basis.

Funding & terms

Type
Unknown
Amount
—
Duration
—
Programme
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Programme and admissions

Admissions not verified

A catalogue listing does not mean applications are open or funding is guaranteed. Check the source for your intake.

Intake
Not confirmed by the source
Duration
Not confirmed by the source
Teaching language
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Taught / research mode
Not confirmed by the source
Study mode
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Campus
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Prerequisites
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Application instructions
Not confirmed by the source
Tuition
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Funding
Not confirmed by the source

How to apply

Deadline: unknown

Applicants must submit an application through Murdoch University’s official postgraduate portal. Required documents typically include academic transcripts, proof of degree completion (if applicable), a personal statement, and any additional materials specified for the chosen admission pathway. International applicants may also need to provide evidence of English proficiency.

Documents required
  • Academic transcripts (Bachelor’s or four-year Engineering degree)
  • Proof of degree completion (if applicable)
  • Personal statement or statement of purpose
  • Evidence of industrial experience (if applicable)
  • Additional specified units’ transcripts (if conditionally admitted)
  • English proficiency test results (if applicable)
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