Johns Hopkins University

An exciting opportunity has arisen to join the team working to deliver a Strategic Major Programme (SMP) to reframe the position of Professional Services within the University. We are seeking a highly skilled and experienced Change Manager, who will play a pivotal role in driving and embedding change across the programme. About the Role As Change Manager you will lead the development and delivery of the programme’s change management approach, supporting the successful implementation of transformation activities across Professional Services. Working closely with the Programme Leads, Programme Manager, Programme Communications Lead, workstream leads and stakeholders across the University, you will ensure that change is effectively planned, communicated and embedded. You will be responsible for assessing the impact of change, developing and delivering change plans, and supporting colleagues to adopt new ways of working. You will also work closely with communications colleagues and workstream teams to ensure alignment between delivery activity and change interventions. This is a high-impact role where you will shape how change is experienced across the organisation, helping to build buy-in, minimise resistance and ensure that programme benefits are realised. About You You will be an experienced change professional with demonstrable success in delivering organisational change in complex environments. You will have a strong understanding of change management principles and methodologies, and experience of applying these in practice to support large-scale transformation programmes. You will bring excellent stakeholder engagement and influencing skills, with the ability to build relationships, challenge constructively and support leaders and colleagues through change. You will be proactive, empathetic and solutions-focused, with the ability to balance strategic thinking and hands-on delivery. For an informal discussion about this post, please contact Abi Clark, Senior Executive Officer (Professional Services) at A.Marsh@soton.ac.uk.

Schemes of Service: Research Division: Engineering Employment Type: Fixed Term As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to develop industry-relevant applied research skillsets while working on translational robotics and AI projects. The primary responsibility of this role is to support a joint SIT–DSO research project focused on evaluating and developing humanoid robot capabilities for door opening and doorway traversal in human-centric environments. The Research Engineer will contribute to humanoid robot system integration, teleoperation-based data collection, simulation-based synthetic data generation using NVIDIA Isaac Sim, and learning-based policy development for manipulation and locomotion tasks. The role will involve both experimental robotics work and AI model development for sim-to-real humanoid manipulation research. Key Responsibilities Participate in and manage the research project together with the Principal Investigator (PI), Co-PI, and research team members to ensure project deliverables are achieved. Undertake the following responsibilities in the project: i. Humanoid Robot System Integration Configure and integrate humanoid robot hardware and software systems for door opening and doorway traversal tasks. Support calibration, perception, locomotion, manipulation, and control pipeline integration. ii. Experimental Testbed Development Design and set up representative door interaction experimental environments. Conduct baseline testing and benchmarking for humanoid manipulation and traversal tasks. iii. Teleoperation and Data Collection Develop and operate teleoperation pipelines for humanoid robot data collection. Collect, process, and manage robot demonstration datasets including perception, robot states, and control data. iv. Simulation and Synthetic Data Generation Develop simulation environments and synthetic data generation workflows using NVIDIA Isaac Sim and Omniverse technologies. Implement domain randomization and scenario variation pipelines for robust sim-to-real learning. v. AI Model Development Support development and evaluation of learning-based control policies using reinforcement learning, imitation learning, and visuomotor learning approaches. Assist in model training, testing, benchmarking, and deployment on real robotic platforms. vi. Research and Technical Reporting Conduct literature reviews and experimental studies related to humanoid robotics and sim-to-real learning. Prepare technical reports, publications, and presentation materials for project reviews and dissemination. Carry out Risk Assessment and ensure compliance with Workplace Safety and Health regulations. Coordinate procurement and liaison with vendors/suppliers. Work independently and within a multidisciplinary team to ensure proper operation and maintenance of robotics equipment and experimental infrastructure. Assist in co-supervision of Final Year Project (FYP) or capstone students together with the project PI. To communicate and liaise with internal and external stakeholders to ensure project deliverables are met. Any other ad-hoc duties assigned by Supervisors. Key Requirements Bachelor’s, Master’s, or PhD degree in Robotics, Mechanical Engineering, Electrical Engineering, Computer Science, or related fields. Experience in robotics software development using ROS/ROS2. Experience with robotic simulation platforms such as NVIDIA Isaac Sim, Isaac Lab, Gazebo, or MuJoCo. Familiarity with humanoid robots, robotic manipulators, or locomotion systems. Knowledge of machine learning, reinforcement learning, imitation learning, or computer vision techniques for robotics applications. Strong analytical and problem-solving skills. Good written and verbal communication skills. Ability to work independently and collaboratively in multidisciplinary teams. The following will be advantageous: Experience with teleoperation systems and data collection pipelines. Experience with NVIDIA Omniverse or sim-to-real workflows. Experience with reinforcement learning frameworks or visuomotor policy training. Experience working with dexterous hands or humanoid manipulation platforms. Key Competencies Strong interest in robotics and embodied AI research. Able to build and maintain strong working relationships with internal and external stakeholders. Self-directed learner with strong initiative and ownership of work. Strong analytical and critical thinking skills. Proficient in technical writing and presentation. Able to work effectively in experimental and rapidly evolving research environments.

Schemes of Service: Faculty Division: Engineering Employment Type: Permanent, Fixed Term The Singapore Institute of Technology (SIT) is Singapore’s first University of Applied Learning, offering industry-relevant degree programmes that prepare its graduates to be work- and future-ready professionals. Its mission is to maximise the potential of its learners and to innovate with industry, through an integrated applied learning and research approach, so as to contribute to the economy and society. The university’s unique pedagogy integrates work and study, embracing authentic learning in a real-world environment through collaborations with key strategic partners. Its focus on applied research with business impact is aimed at helping industry innovate and grow. SIT’s centralised campus within the Punggol Digital District (PDD) provides a vibrant ecosystem where academia, industry, and the community are tightly integrated. SIT espouses an applied learning approach with a strong focus on science and technology. Faculty work closely with industry on translational research and innovation, providing solutions to real-world challenges through applied research, workforce development, and system deployment. As part of its strategic growth in quantum technologies, SIT is expanding its capabilities in Applied Quantum Computing, with a focus on developing hybrid quantum-classical solutions that deliver tangible industry value in the short to medium term. This includes applications combining quantum computing, artificial intelligence (AI), and high-performance computing (HPC), as well as quantum-inspired algorithms and quantum machine learning (QML). Responsibilities: Lead and contribute to applied quantum computing research projects with industry partners. Develop hybrid quantum-classical applications integrating AI and HPC workflows. Apply VQE, QAOA, QML, quantum annealing, and quantum-inspired algorithms. Develop industry-relevant use cases for near-term quantum advantage. Develop and teach quantum computing courses (CET/PET and undergraduate). Supervise capstone projects and industry-linked research. Engage with the quantum ecosystem and contribute to SIT initiatives. Qualifications: PhD in Quantum Computing, Physics, Computer Science, Engineering, or related field. 2–5 years of relevant experience after PhD (industry or applied postdoctoral research). Expertise in quantum algorithms and NISQ computing. Experience with hybrid quantum-classical workflows. Proficiency with Qiskit, PennyLane, CUDA-Q or equivalent. Strong programming skills and familiarity with AI/ML tools. Experience in industry collaborations and applied research is preferred. What SIT offers: An applied research environment focused on real-world impact. Opportunities to work with leading quantum industry partners. Access to Punggol Digital District ecosystem and testbeds. Role in building Singapore’s applied quantum capability. Opportunities to develop new programmes aligned with industry needs. Competitive environment in a global innovation hub. How to apply: Curriculum vitae Cover letter Research statement (max 2 pages) Teaching statement (max 1 page) Three representative research outputs