Kyoto University of Foreign Studies

With over 85 years of rich heritage, The Hong Kong Polytechnic University (PolyU) has evolved alongside society and made pivotal contributions to the development of Hong Kong, the Nation and the world. The University pursues world-class excellence in education, research and knowledge transfer to nurture socially responsible professionals and leaders, as well as to drive impactful research and innovation. PolyU will strive to continually excel as an innovative world-class university that makes a positive impact on society, living up to the University’s motto: “To learn and to apply, for the benefit of mankind”. Ranked among the top 100 universities globally by well-known ranking organisations such as Quacquarelli Symonds (QS), Times Higher Education (THE) and U.S. News & World Report, PolyU offers a wide range of world-class educational and research programmes in seven faculties and three independent schools. PolyU has furthermore achieved commendable results in the QS World University Rankings by Subject 2025 – it is ranked in the global top 30 for seven subjects, is first in Hong Kong for three subjects, and is in the global top 100 for 26 subjects. For further details about the University, please visit PolyU’s website at https://www.polyu.edu.hk/. DEPARTMENT OF APPLIED MATHEMATICS Research Assistant Professor in Optimization and Operations Research / Statistics and Data Science / Financial Mathematics / Engineering and Computational Mathematics / Mathematical Science (several posts) (Ref. 260305001) The Department of Applied Mathematics (AMA) is one of the constituent departments of the Faculty of Computer and Mathematical Sciences. Apart from making a significant contribution to most of other academic programmes of the University by providing service teaching, the Department also offers master programmes in Applied Mathematics for Science and Technology, Operational Research and Risk Analysis and Quantitative Finance and FinTech. Starting from 2025/26 academic year, the Department offers a new Bachelor Scheme in Applied Mathematics and Finance Analytics and Fast-track Integrated Bachelor’s and Master’s Degree Programmes and will launch a new master programme, MSc in Mathematics for Artificial Intelligence Technology in 2026/27. Members of the Department have expertise in applied optimization and optimal control, engineering computation, operational research, management science and applied statistics, FinTech, data science and machine learning. There are currently 54 academic staff and about 105 research personnel in the Department. Please visit the website at https://www.polyu.edu.hk/ama for more information about the Department. The Department has established Joint Laboratory of Applied Mathematics with the Academy of Mathematics and Systems Science of the Chinese Academy of Sciences (JLab), CITIC-PolyU Interdisciplinary Mathematical Digital AI Joint Laboratory (AIJLab) and Mathematical Optimization Innovation Laboratory with Huawei. The appointees are expected to be actively involved in the activities of the Laboratory. Duties The appointees will be required to: (a) conduct research as the main duty and actively pursue external research grants, such as General Research Fund, as Principal Investigator or Co-Investigator; (b) provide quality teaching at undergraduate or postgraduate level; (c) contribute to departmental service; and (d) perform any other duties as assigned by the Head of the Department or his delegates. Qualifications Applicants should: (a) have a PhD degree in Mathematics / Statistics / Financial Mathematics / Operations Research / Computational Mathematics / Applied Mathematics or a closely related field with experience in Data Science and Analytics; (b) preferably have at least two years of relevant postdoctoral research experience; (c) have demonstrated promise of a high level of creativity in research and teaching in some subdivisions of his/her field; (d) be able to demonstrate effective classroom teaching; and (e) be highly proficient in written and spoken English. Application Please submit an application through PolyU’s career website (https://jobs.polyu.edu.hk/rap). Consideration of applications will commence on 26 March 2026 until the positions are filled. The University’s Personal Information Collection Statement for recruitment can be found at https://www.polyu.edu.hk/hro/careers/pics_for_recruitment/. PolyU is an equal opportunity employer, dedicated to fostering an environment that embraces diversity and demonstrates inclusion of people from all backgrounds, cultures, identities and experiences where all members of the University are treated with fairness, dignity and respect. To learn more about the University’s “Statement on Equal Opportunities, Diversity, and Inclusion”, please visit our website at https://www.polyu.edu.hk/hro/equal_opportunities_diversity_and_inclusion/.

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

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.