Korea Aerospace University

Role Overview As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have opportunities to tackle real-world, industry-relevant problems, working alongside faculty members and professional officers. The SIT Centre for Intelligent Robotics (CIR) is an applied research centre responsible for developing and maintaining core applied robotics and embodied AI capabilities for real-world deployment. CIR is seeking a Robotics Engineer to implement state-of-the-art learning-based robotic manipulation methods on physical platforms for industry-driven applications, with an emphasis on contact-rich manipulation, robustness, and safe operation. The successful candidate will work closely with physical robots to translate recent advances in learning-based robotics into reliable, deployable systems. Key Responsibilities Implement, adapt, and evaluate state-of-the-art learning-based methods (e.g. imitation learning) for contact-rich robotic manipulation. Integrate hardware and software components into a functional system for real-world deployment. Design and execute field trials (test protocols, data logging, troubleshooting, reliability improvements). Produce technical documentation, reports, and implementation guides to support knowledge transfer and maintainability. Support project procurement activities (e.g., technical specifications, vendor evaluation, quotations) for robotics hardware, sensors, and compute resources. Contribute to publications and technical notes to disseminate research outcomes. To communicate and liaise with any internal and external stakeholders to ensure project deliverables are met. Any other ad-hoc duties assigned by supervisor. Requirements Bachelor’s degree or higher in Robotics, Computer Science, Mechanical Engineering, Control Engineering, or a related field. Experience in imitation learning and reinforcement learning for robotics applications. Hands-on familiarity with robotic manipulators and motion planning. Proficiency in deep learning frameworks such as PyTorch or TensorFlow. Experience with ROS / ROS 2 for real-robot software integration. Proficiency in Python and C++, with good software engineering practices (version control, testing, maintainable code). Familiarity with robotics simulation tools such as Gazebo, Isaac Sim, or MuJoCo. At least 2 years of experience in robotics research or industry projects.

The Faculty of Medicine wishes to appoint an NIHR Academic Clinical Lecturer, hosted by one of the following clinical specialties: Public Health, Paediatrics or Ophthalmology. The post is intended for an applicant within any of these three specialities, with the speciality of the final (single) post dependent on the successful applicant. The post-holder will be pursuing their development of research and teaching within either the Primary Care, Population Science and Medical Education school, Human Development and Health school or Clinical and Experimental Sciences school of the Faculty of Medicine, University of Southampton. In this post-doctoral role, the successful candidate will be in specialist clinical training at ST3 level or above and have substantial experience of the relevant research areas, a proven track record of high-quality original research publications, the ability to work well in a multidisciplinary, multi-professional team and hold a corresponding NTN. You will join the NIHR Clinical Integrated Academic Training Programme at the University of Southampton, as an NIHR Academic Clinical Lecturer. The post-holder will also have clinical commitments at University Hospital Southampton NHS Foundation Trust that will lead to the acquisition of clinical skills required for full registration within the specialty. The post is subject to terms and conditions of service determined by the University of Southampton and in its honorary clinical capacity by the University Hospital Southampton Foundation Trust Board. Informal enquiries are welcome and should be addressed to:  Public Health: Professor Simon Fraser, Professor of Public Health - email: s.fraser@soton.ac.uk Paediatrics: Professor Graham Roberts, Professor of Paediatric Allergy & Respiratory Medicine - email: g.c.roberts@soton.ac.uk Ophthalmology: Professor Andrew Lotery, Professor of Ophthalmology - email: a.j.lotery@soton.ac.uk A satisfactory Criminal Records Bureau disclosure at Enhanced level is required for this post. Please note: successful applicants will be appointed to a different salary range (AMNL £46,675 to £80,081) if they were at ST3 on or before 2 August 2016.  The Faculty of Medicine holds an Athena SWAN Silver Award demonstrating commitment to equal opportunities and gender balance in the workplace. The Faculty recognises that applicants may seek flexible working patterns which will be considered as part of the recruitment process. For further information including key benefits designed to help maintain and support employees' well-being and work-life balance, please see our working with us website pages.

Ref.: 536109 Work type: Full-time Department: Faculty of Social Sciences (30000) Categories: Senior Research Staff & Post-doctoral Fellow Applications are invited for appointment as Research Assistant Professor in the HKU Research Hub of Population Studies (the Population Hub), Faculty of Social Sciences (Ref.:536109), to commence as soon as possible, on a two-year fixed-term basis, with the possibility of renewal subject to satisfactory performance and funding availability. This position will immerse the appointees in both academic research and teaching in the multi-disciplinary team of the HKU Research Hub of Population Studies (https://www.socsc.hku.hk/rhps/) within the Faculty of Social Sciences. Duties and Responsibilities The appointees will be primarily responsible for the following: Involve in on-going research projects of the Population Hub Draft proposals, reports, and presentations relevant to the projects Perform advanced quantitative data analysis Publish high-quality academic papers in peer-reviewed journals Mentor junior research staff Teach one undergraduate or taught postgraduate course per year, if required; and Support and perform other duties as assigned Requirements The appointees are expected to have: A Ph.D. degree in the Social Sciences, Sociology, Demography, Statistics, Public Health, Social Work, or a relevant discipline A strong quantitative background and extensive experience in managing and analysing large and complex datasets; expertise in Computational Social Science and proficiency in longitudinal analyses, multilevel modelling, data visualisation, and state-of-the-art statistical models would be an advantage The ability to develop a strong body of high-quality publications in scholarly journals with global impact The ability to multitask and work under tight schedules to meet project deadlines The ability to work independently and collaboratively as part of a team A strong commitment to teaching and training activities in the Population Hub and the Faculty A strong sense of self-motivation, responsibility, and work ethics Good analytical, communication, organizational, and problem-solving skills What We Offer A highly competitive salary commensurate with qualifications and experience will be offered, in addition to annual leave and medical benefits, with a contract-end gratuity and University contribution to a retirement benefits scheme, totalling up to 15% of basic salary. How to Apply The University only accepts online applications for the above post. Applicants should apply online at the University’s Careers site (https://jobs.hku.hk) and upload an up-to-date CV. Review of applications will commence as soon as possible and continue until May 15, 2026, or until the post is filled, whichever is earlier. The University is an equal opportunities employer and is committed to equality, ethics, inclusivity, diversity and transparency