Lawrence Technological University

As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skill sets that are relevant to industry demands while working on research projects in SIT.  The primary responsibility of this role is to support and contribute to an industry innovation research project. The Research Engineer will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep learning-based computer vision algorithms and software for object detection, classification, and segmentation. Key Responsibilities Participate in and manage the research project together with the PI, Co-PI, and research team to ensure timely achievement of project deliverables. Undertake the following specific responsibilities in the project: i. Develop, train, and optimise deep learning models for object detection, classification, and segmentation using real-world datasets. ii. Design and implement software modules to integrate the models into a working system prototype. iii. Perform data annotation. iv. Conduct experiments, analyse results, and iterate models for improved accuracy and efficiency. v. Prepare project documentation, technical reports, and academic publications. vi. Collaborate with industry partners and contribute to technology transfer efforts. Job Requirements 1. Possess strong technical knowledge and hands-on experience in: Deep learning frameworks (e.g., PyTorch, TensorFlow) Deep learning models (e.g., YOLO, U-Net, EfficientNet, ResNet, FPN, Fast R-CNN) Computer vision techniques and algorithms Python and relevant libraries (e.g., PyQt, OpenCV, NumPy, scikit-learn), particularly for developing Windows desktop application software incorporating deep learning models 2. Hold at least a Bachelor’s degree in Computer Science, Electrical/Electronic/Software Engineering, or a related field. A Master’s or PhD degree in relevant areas will be advantageous. 3. Familiarity with the following areas is advantageous: Participation in Kaggle competitions, showcasing practical problem-solving and model development skills Model deployment (e.g., ONNX, TensorRT) Edge computing or embedded vision systems (e.g., NVIDIA Jetson Nano) Real-time processing and GPU acceleration Experience working on industry R&D projects Key Competencies Able to build and maintain strong working relationships with team members, stakeholders, and external partners Self-motivated and committed to continuous learning and improvement Proficient in technical writing & presentation, research reporting, and academic publication Possess strong analytical, problem-solving, and critical thinking skills Demonstrate initiative and ownership in carrying out tasks independently

Location: SIT Punggol Campus Job Type: Contract Experience Level: 3+ years relevant experience (preferred) About Us: Autonomous Systems Advanced Intelligence Laboratory (ASAIL) is at the forefront of developing next-generation unmanned aerial capabilities for the public safety sector. We are bridging the gap between commercial drone hardware and the demanding requirements of law enforcement and security operations. Our mission is to enhance the safety and effectiveness of personnel through intelligent, resilient, and autonomous aerial systems. We are currently seeking a highly motivated Research Engineer to lead the applied research and development of advanced control augmentation techniques for Commercial Off-The-Shelf (COTS) drones. This role focuses on pushing the limits of COTS hardware by integrating sophisticated software and edge computing solutions. The Role: As our Research Engineer, you will be responsible for the end-to-end development of augmentation software, from theoretical design and simulation to real-world proof-of-concept demonstrations. You will work on a portfolio of critical enhancements, including advanced navigation algorithms, swarm intelligence, cyber security hardening, and payload-specific control systems. Key Responsibilities: Control Augmentation Development: Design, implement, and tune advanced control augmentation techniques (e.g., model predictive control, adaptive control) to enhance the stability and agility of COTS drones under dynamic conditions. Swarm Intelligence: Develop and test decentralized swarm algorithms for coordinated area search, target tracking, and collaborative task allocation without reliance on constant ground control intervention. Cyber Security Enhancement: Research and implement mitigation strategies against common attack vectors on COTS platforms, including GPS spoofing, communication jamming, and protocol vulnerabilities. Develop hardened communication layers between the drone, edge device, and ground station. Payload-Specific Control: Integrate and tune control systems for mission-specific payloads (e.g., gimbaled cameras, spotlights, delivery mechanisms) to ensure stable operation and precise control during flight. Edge Computing Implementation: Architect and deploy machine learning and computer vision models directly onto onboard edge devices (e.g., NVIDIA Jetson) for real-time object detection, tracking, and autonomous decision-making. Proof-of-Concept Demonstration: Lead the integration of software onto physical drone platforms, conduct rigorous flight testing, and execute live demonstrations to validate performance against operational requirements. Documentation & Dissemination: Document research findings, software architectures, and test results. Prepare reports and presentations for internal and external stakeholders. Required Qualifications & Expertise: Education: Honor’s degree (Master’s and Ph.D. preferred) in Robotics, Computer Science, Electrical Engineering, Aerospace Engineering, or a related field. Control Theory: Strong theoretical and practical background in control systems, including PID, LQR, MPC, or adaptive control. Robotics Software: Extensive experience with the Robot Operating System (ROS/ROS 2). Programming: High proficiency in C++ and Python for real-time robotic applications. Simulation: Experience with realistic simulation environments such as Gazebo, AirSim, or Unreal Engine. Edge Computing: Proven experience deploying algorithms on resource-constrained edge devices for real-time inference and control. Drone Platforms: Hands-on experience with commercial autopilots (PX4, ArduPilot) and integrating software with COTS frames (DJI, Holybro, etc.) via companion computers. Swarm Robotics: Familiarity with consensus algorithms, formation control, and communication protocols for multi-agent systems. Security: Understanding of wireless communication protocols (Wi-Fi, 4G/5G, MAVLink) and common cybersecurity vulnerabilities in drone systems. Preferred Skills (Bonus): Experience in law enforcement, defense, or public safety technology projects. Knowledge of computer vision techniques for object detection and tracking (YOLO, OpenCV). Experience with RF signal analysis or spectrum monitoring.

Enjoy the benefits of a large community minded organisation and a friendly, flexible work environment (including a hybrid work model) Rewarding role working directly with our students to support their study success Join a dedicated and supportive team committed to delivering high quality, student centred learning experiences The role Full Time, Continuing Level 6 - $92,025 to $99,538 pa (plus 17% superannuation) Albury-Wodonga, Bathurst, Dubbo, Orange or Wagga Wagga In this role you will be a vital advocate for student success. Your primary focus will be on providing individualised and group support to help students navigate subject content, concepts, and assessments. Through providing initial assessment feedback to students on academic literacy and numeracy, you will be empowering students to recognise and build on their unique strengths, and guiding them towards additional support services when necessary. This is a student facing role which requires an on-campus presence and as such, remote work is not available. About you Highly developed communication and interpersonal skills Proven ability to prioritise work, meet deadlines and produce high quality outcomes Strong technology skills to support students and operate effectively in a physically distributed team The successful applicant will be required to produce, satisfy and maintain a "Working with Children Check", in accordance with the Commission for Children and Young People Act (NSW). About us We are a university of the land and people of our regions. True to the character of regional Australia we have gumption, we have soul and we collaborate with others. We develop holistic, far-sighted people who help their communities grow and flourish. The Wiradjuri phrase yindyamarra winhanganha means the wisdom of respectfully knowing how to live well in a world worth living in. This phrase represents who we are at Charles Sturt University - our ethos. It comes from traditional Indigenous Australian knowledge, but it also speaks to the mission of universities - to develop and spread wisdom to make the world a better place. Harnessing technology, we thrive as a distributed yet connected community, welcoming and engaging with people across Australia and the world. Learn more about the Division of Student Success here. Visit our website to learn about our great range of employee benefits. Charles Sturt University is committed to building a diverse workforce as shown through our Athena Swan Bronze Award, our Australian Workplace Equality Index Bronze Award and our membership of a range of diversity focused organisations including Diversity Council Australia and Pride in Diversity. We encourage applications from First Nations people, carers, people from culturally and linguistically diverse backgrounds, people with disability, neurodivergent people, and people of all age groups, genders and sexualities for all roles. To apply Click the Apply button and complete your application online, and address the selection criteria in the position description and upload your CV. If you experience difficulties applying online or for further information on completing the application process please visit our how to apply page or contact us. This position is open to Australian Citizens and Permanent Residents; or applicants who hold a current valid work visa commensurate with this position. Further information Additional information is available in the position description or by contacting: Jo Blatch | Senior Manager, Student Success Services | jblatch@csu.edu.au Closing Date: 11pm, 22 March 2026