University of Reading

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.

Doctoral position at Department of Electronics and Nanoengineering at Aalto University, in Espoo, Finland. DC2: Sub-terahertz and terahertz reconfigurable intelligent surfaces Main supervisor:  Prof. Viktar Asadchy[AALTO] Co-supervisors/mentors:  Dr. Victoria Tormo [INDRA] and Dr. Barthès [3DEUS] Objectives To establish an analytical modeling approach for multilayer tunable metasurfaces that captures the key electromagnetic coupling effects between layers and enables fast prediction of their tunable response without relying solely on full-wave simulations. To create efficient adjoint-based optimization methods for tunable metasurfaces that provide rapid sensitivity/gradient evaluation, support high-dimensional design spaces, and allow systematic optimization of performance targets such as efficiency, bandwidth, and multi-condition operation. To design and fabricate reconfigurable metasurface prototypes that implement a global tuning mechanism, and to experimentally characterize their electromagnetic performance. To validate the achieved tuning range and functional performance in laboratory measurements against modeling and simulation results. This position is part of the MetaTune Doctoral Network "Reconfigurability using inversely designed metasurfaces", which has been funded under the Horizon Europe Marie Skłodowska-Curie Actions (MSCA) program. Acquire knowledge During the thesis, the candidate will acquire a solid understanding of the theoretical and practical requirements for designing tunable and reconfigurable metasurfaces, with emphasis on multilayer architectures and system-level performance metrics (efficiency, bandwidth, angular response, and robustness). In parallel, the candidate will gain in-depth knowledge of analytical modeling techniques and adjoint-based optimization methods for high-dimensional inverse design, as well as develop practical expertise in prototyping and laboratory characterization. Go to the project webpage for more information What METATUNE Offers Work contract at Aalto is for 36 months funded through the MSCA network, with the additional benefits for employees (public and universal health system, free schools, etc.). Two 3-month research stays, one at Indra Sistemas SA in Madrid and one in 3DEUS Dynamics SAS at Lyon are foreseen in the research plan. Opportunity to pursue a PhD degree at a leading European university within a collaborative, international network. Training program including research-specific and transferable skills courses. Active participation in workshops, conferences, and network-wide events to build professional and scientific connections. Stimulating, multidisciplinary, and international research environment within a prestigious European training network. Starting date: Now-December 2026; negotiable. Deadline for online application: May 31, 2026 (but candidates are encouraged to apply as soon as possible). Requirements Mandatory Requirements You must have a finalized master’s degree in fields related to the research topic: Electrical Engineering, Physics, Telecommunications Engineering, Applied Physics, Optics, Material Engineering, or similar. You should not have a doctoral degree at the time of recruitment. You must not have resided or carried out your main activity (work, studies, etc.) in Finland for more than 12 months in the 36 months immediately before the recruitment (this is a requirement from the funding authority). You will apply for the study right in doctoral studies at Aalto University School of Electrical Engineering and must satisfy the eligibility conditions for this doctoral programme. Sufficient skills in the English language. Additional Requirements Strong background in electrodynamics and excellent mathematical skills. Basic knowledge of computational electromagnetics. High proficiency in Python, MATLAB, Wolfram Mathematica, or similar programming software. High motivation and creativity. Good written and verbal communication, including presentation skills. Good organizational skills, attention to details, and ability to meet deadlines. Willingness to learn and work collaboratively in a research environment. Desired skills and knowledge Proficiency in electromagnetic simulation software, such as COMSOL Multiphysics, ANSYS HFSS, or CST Studio Suite. Solid knowledge of computational electromagnetics. Previous experience with design and fabrication of metasurfaces. Apply now via this link, at the latest by May 31st, 2026: https://metatune.webs.upv.es/jobs/

Relocation support to help you settle into the stunning Orange region Access salary packaging and staff discounts with partnering corporates Join a dynamic and innovative physiotherapy team The role Continuing, full time (part time hours considered) Academic Level B/C - $113,841 to $160,308 pa (plus 17% superannuation) Location: Orange, NSW We are seeking an experienced physiotherapy professional to join the School of Allied Health, Exercise and Sports Sciences to actively deliver high quality teaching, contribute to curriculum development and foster student engagement using blended subject delivery modes. The successful candidate must have significant experience in contemporary musculoskeletal physiotherapy practice in an Australian context. The successful candidate must also have the capacity to teach across other areas of physiotherapy practice and a commitment to regional, rural and remote health and practice. About you A physiotherapy qualification A physiotherapy qualification appropriate to the level being applied for or equivalent accreditation and standing. Current practising registration as a Physiotherapist with the Australian Health Practitioner Regulation Agency (Ahpra). Additional qualification appropriate to the level being applied for or equivalent accreditation and standing. Significant experience in contemporary musculoskeletal physiotherapy practice in an Australian context. Sound knowledge of the discipline, including digital health and culturally safe health care, and experience in physiotherapy practice and research in rural and regional contexts. Commitment to delivering high-quality student-centred learning and teaching. 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 Faculty of Science and Health here. Learn more about the School of Allied Health, Exercise and Sports Sciences 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(s) Level B - Lecturer Level C - Senior Lecturer or by contacting: Dr Cherie Zischke | Course Director and Lecturer in Physiotherapy | czischke@csu.edu.au | Ph: 02 6582 9465 Closing Date: 11pm, 6 April 2026