Rmit

Education

ResearchAssistant,ImageProcessing

$81–81k Melbourne, Australia FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid+ candidates.

The Brief

“Research Assistant, Image Processing at Rmit. Skills: Image Processing, Computer Vision, Machine Learning, Deep Learning, Photonics, Integrated Photonic Systems, On-chip Optical Technologies, Light-matter Interaction. Work on photonics and integrated photonic systems, including on-chip optical technologies and light–matter interaction at micro- and nanoscale levels.. Support research that spans both fundamental studies and applied outcomes, with applications in energy systems, environmental moni”

Industry & Context.

Education
Problems you'll solve

Problem-solving abilities for determining innovative solutions to the complex problems common to computer vision engineering – such as dealing with messy background or addressing issues with object detection.

Eligibility Requirements

May be required to work and/or be based at other campuses of the University, Passing a Working with Children and National Police Check

What They're Looking For.

Must Have

Ph. D. degree in Optical engineering, Applied Physics, or Computer Science, Proficiency in programming languages, including Python, C++, or Java, focusing on algorithms and data structures applied explicitly in computer vision projects, Knowledge of machine learning and deep learning frameworks, including TensorFlow or PyTorch, Knowledge of neural networks – especially convolutional neural networks (CNNs), Understanding of image processing techniques – including filtering, edge detection, and image segmentation– for manipulating images, Familiarity with computer vision libraries, like OpenCV or Dlib, for developing and implementing vision-based models, Familiar with 3D refractive imaging technique with demonstratable track record., Mathematical skills in linear algebra, calculus, and statistics for algorithm development and data analysis, Problem-solving abilities for determining innovative solutions to the complex problems common to computer vision engineering – such as dealing with messy background or addressing issues with object detection., Attention to detail for ensuring precision in coding and model training – and enhancing the accuracy and reliability of computer vision applications., Collaborative skills for working effectively with data scientists, software developers, and project managers., Adaptability, including a willingness to stay updated with the rapidly evolving field of computer vision and learn new techniques and technologies as they emerge., Communication skills for explaining technical project requirements, progress, and outcomes to non-technical stakeholders, Passing a Working with Children and National Police Check

Nice to Have

Evidence of research output including high quality publications, conference contributions and/or technical reports in the field., Ability to generate alternative funding projects through effective liaison with industry and government.

What You'll Do.

Work on photonics and integrated photonic systems

including on-chip optical technologies and light–matter interaction at micro- and nanoscale levels.

Support research that spans both fundamental studies and applied outcomes

with applications in energy systems

environmental monitoring

advanced manufacturing

and controlled environment agriculture.

How You'll Work.

Team & Collaboration

Ability to work autonomously whilst displaying a commitment to work in a team environment, including the demonstrated ability to confidently and effectively work with colleagues, project team leaders, and industry partners; Collaborative skills for working effectively with data scientists, software developers, and project managers.

Communication Scope

Demonstrated high level of communication skills; Communication skills for explaining technical project requirements, progress, and outcomes to non-technical stakeholders

Process & Methodology

Ability to meet deadlines, Effectively manage varying workloads, Respond to changing priorities as required.

Full Job Description

## Overview: * **1 x full time, fixed term (2 years) position available in the School of Science within STEM College** * **Salary Academic Level A ($80,755****\- $109,536) + 17% Superannuation** * **Based at the City, but may be required to work and/or be based at other campuses of the University** **About the Role** The Research Assistant will work on photonics and integrated photonic systems, including on-chip optical technologies and light–matter interaction at micro- and nanoscale levels. The role is part of the ARC E2Crop Hub and the Centre for Atomaterials and Nanomanufacturing at RMIT University. These programs focus on developing technologies for energy-efficient systems, renewable energy integration, advanced materials, sensing, and sustainable production. The position involves supporting research that spans both fundamental studies and applied outcomes, with applications in energy systems, environmental monitoring, advanced manufacturing, and controlled environment agriculture. **About You** * Proficiency in programming languages, including Python, C++, or Java, focusing on algorithms and data structures applied explicitly in computer vision projects * Knowledge of machine learning and deep learning frameworks, including TensorFlow or PyTorch * Knowledge of neural networks – especially convolutional neural networks (CNNs) * Understanding of image processing techniques – including filtering, edge detection, and image segmentation– for manipulating images * Familiarity with computer vision libraries, like OpenCV or Dlib, for developing and implementing vision-based models * Familiar with 3D refractive imaging technique with demonstratable track record. * Mathematical skills in linear algebra, calculus, and statistics for algorithm development and data analysis * Evidence of research output including high quality publications, conference contributions and/or technical reports in the field. * Ability to generate alternative funding projects through effective l

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