University of Houston

Role Overview As a University of Applied Learning, Singapore Institute of Technology (SIT) works closely with industry partners to develop applied research capabilities that translate directly into real-world deployment. Our research staff are equipped with industry-relevant skills through hands-on work on operational research platforms and systems. The SIT Centre for Intelligent Robotics (CIR) is a strategic capability centre under RoboPrecinct@Punggol Digital District (PDD), responsible for developing and sustaining the simulation, digital twin, and embodied AI foundations required for precinct-level deployment of robotic systems. We are seeking a Robotics Simulation Engineer to support the Centre’s robotics and embodied AI initiatives. This role focuses on the design, implementation, and maintenance of multi-platform robotics simulation environments, supporting research, development, testing, and Sim2Real transfer of robotic systems. The successful candidate will work across NVIDIA Isaac Sim, Gazebo, MuJoCo, and related simulation platforms, enabling scalable experimentation and robust system-level evaluation prior to real-world deployment. Key Responsibilities Develop, configure, and maintain robotics simulation environments across multiple platforms, including NVIDIA Isaac Sim, Gazebo, MuJoCo, and other relevant simulators for different applications and robotics platform Design modular and reusable simulation assets for robots, environments, sensors, and physics configurations. Integrate robotic platforms into simulation, including URDF/SDF workflows, articulation setup, and validation of kinematics and dynamics. Configure and tune physics simulation parameters (contacts, friction, joint limits, control rates, solver settings) to ensure realistic robot behaviour. Develop and maintain sensor simulation pipelines (RGB, depth, RGB-D, LiDAR, IMU) for perception and learning-based robotics. Support simulation-to-real (Sim2Real) workflows, including domain randomization, sensor noise modelling, and reality-gap mitigation. Integrate simulations with ROS / ROS 2 for closed-loop robot control, testing, and benchmarking. Automate simulation setup, execution, and experiment management using Python and C++, supporting batch experiments and data collection. Support system-level experimentation, benchmarking, and iterative improvement of embodied AI and robotic applications. Prepare technical documentation, simulation guidelines, and reusable templates to support knowledge transfer and long-term maintainability. Provide mentorship to undergraduate students in projects. Carry out risk assessment, and ensure compliance with Work, Safety and Health Regulations. Prepare technical documentation, reports, and implementation guides to support knowledge transfer and long-term maintainability. Contribute to publications and technical notes to disseminate research outcomes. The employee is to communicate with any relevant internal or external stakeholders to ensure project deliverables are met. Any other adhoc duties assigned by supervisor. Requirements Bachelor’s degree or higher in Robotics, Computer Science, Mechanical Engineering, Control Engineering, or a related discipline. Hands-on experience with at least two robotics simulation platforms, such as NVIDIA Isaac Sim, Gazebo, or MuJoCo. Practical experience working with URDF and/or SDF robot models and simulation integration. Working knowledge of robotics physics and dynamics, including articulated systems. Experience integrating simulation environments with ROS or ROS 2. Proficiency in Python, with working knowledge of C++ for simulation or robotics software development. Minimum 2 years of experience in robotics simulation, robotics research, or industry-based robotics projects. Preferred Skillsets (Advantageous) Experience with USD-based workflows and Omniverse-based simulation environments. Familiarity with PhysX and/or other physics engines used in robotics simulation. Experience supporting Sim2Real pipelines for real-robot deployment. Exposure to reinforcement learning, imitation learning, or learning-based control in simulation. Experience working with mobile manipulators, humanoid robots, or legged robots. Familiarity with GPU-accelerated simulation, performance optimisation, and Linux-based systems.

Associate Professor (Infectious Diseases Modelling) A unique opportunity to work across UWA and The Kids Research Institute Australia, combining world-class modelling expertise with clinical and public health partnerships to deliver real-world impact for Western Australia. Lead and grow an internationally recognised research program in infectious disease modelling, including mentoring researchers and building modelling capability across Western Australia. The successful applicant will hold an honorary appointment with The Kids Research Institute Australia, enabling integration into a leading child health research environment and access to collaborative infrastructure. Full-time appointment on a fixed term basis for 5 years Base salary range: Level D, $173,024 – $190,355 p.a. (pro-rata) plus 17% superannuation. About the area The UWA School of Physics, Mathematics and Computing combine Departments with strong identities and histories going back to the beginnings of UWA. Research and education in the School spans these departments to make advances in both theoretical and applied domains, including the development of new models, data analyses, and software to solve pressing real-world problems. Our work supports important collaborations with international partners, industry, hospitals, and community stakeholders, generating high quality publications, patents, and spin-out companies. About the opportunity Develop and apply advanced mathematical, computational and statistical models for infectious diseases (e.g., COVID-19, influenza, RSV), drive epidemic forecasting and analytics in Western Australia, secure competitive funding, publish in leading journals, and build national and international collaborations. Lead curriculum development and coordination of Infectious Disease Modelling, contribute to undergraduate and postgraduate teaching, and supervise and mentor Honours, Master’s, PhD students and early-career researchers to build modelling capacity in WA. Support the Chair in establishing an internationally recognised research program, foster interdisciplinary partnerships (including with The Kids Research Institute Australia and ACEFA), engage with community and industry stakeholders, uphold University governance and inclusion commitments, and contribute to service, IP management and research translation. About you PhD in an academic field relevant to the discipline or other higher professional qualifications appropriate to their discipline. An excellent professional and academic record. Demonstrated experience of leading and engaging an inclusive and diverse team based on research outcomes and outputs and the ability to drive collaborations with other research groups and organisations, and across government organisations or industry. Commitment to build world class research capacity at UWA. An outstanding track record in excellence in research at a national or international level evidenced by a series of peer-reviewed journal articles in the field of infectious disease modelling, published in high quality journals.     Evidence of ability to teach infectious disease modelling. Demonstrated ability to positively contribute to team, school and wider University activities such as team and school meetings, strategic planning and program development.   Note: Employment checks will include information on gender-based violence, sexual harassment, and related misconduct to meet legal obligations. A current National Police Clearance will be required by the successful applicant. Position description: PD Associate Professor 522764.docx To learn more about this opportunity, please contact Professor Nick Golding at nick.golding@uwa.edu.au cc’ing in Natasha Stretton at natasha.stretton@uwa.edu.au How to apply Please apply online via the Apply Now button and address the selection criteria in your submission in a separate document. For information to assist you with compiling statements to answer the selection criteria, please visit Addressing the selection criteria. You may submit a statement describing any personal circumstances relevant to your application. This can include academic/professional interruptions or achievements relative to opportunity. Closing date: 11:55 PM AWST on Wednesday 1 April 2026 This position is open to international applicants. Benefits Flexible working options. Generous paid leave including parental leave. Up to 17% employer paid superannuation. Salary packaging available. Incremental progression based on 12 months continuous service. Discounted UWA course fees. Discounted health insurance. Employee Assistance Program. About the University The University of Western Australia (UWA) is ranked among the top 100 universities in the world and a member of the prestigious Australian Group of Eight research intensive universities. With a strong research track record, vibrant campus and working environments, supported by the freedom to innovate and inspire, there is no better time to join Western Australia’s top university. Learn more about us. Our commitment to inclusion and diversity UWA is committed to a diverse workforce and an equitable and inclusive workplace. We are committed to fostering a safe environment for all, including Aboriginal and Torres Strait Islander people, women, those from culturally and linguistically diverse backgrounds, the LGBTIQA+ community, and people living with disability. If you require any reasonable adjustments, we encourage you to advise us at the time of application. Alternatively, you can contact us for assistance during the recruitment process. If you have queries relating to your application, please contact the individual named in the advertisement. Alternatively, please contact the Talent team at people@uwa.edu.au with details of your query. To enable a quick response, please include the 6-digit job reference number.

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.