Golestan University

Ref.: 534420 Work type: Full-time Department: Department of Obstetrics and Gynaecology, School of Clinical Medicine (20900) Categories: Professoriate Staff Applications are invited for appointment as Tenure-Track Clinical Professor (several posts) in the Department of Obstetrics and Gynaecology, School of Clinical Medicine (Ref.: 534420), to commence as soon as possible, on a four-year fixed-term basis, with the possibility of renewal and consideration for tenure before the expiry of a second four-year fixed-term contract, subject to satisfactory performance. Exceptionally outstanding candidates may be considered for appointment on tenure terms. The Department is seeking for candidates from the following disciplines within the scope of obstetrics and gynaecology to join our team: General Gynaecology, Gynaecological Oncology, Reproductive Medicine & IVF, General Obstetrics, High Risk Obstetrics, Fetal Medicine, and Prenatal Diagnosis. Applicants should hold a specialist registration with the Medical Council of Hong Kong or be eligible to apply to the Hong Kong Academy of Medicine for the Certification of Specialist Registration, and possess other relevant higher academic qualifications (e.g., MD, MS, PhD). They should have a distinguished and sustained record of high-quality impactful research (basic science, translational and/or clinical research), with demonstrated clinical excellence. They should also have achieved international recognition for their scholarship and professional expertise. In addition, applicants must have an outstanding and consistent record of excellence in teaching and learning and/or knowledge exchange, services and administration. Preference will be given to those with demonstrated administrative leadership and management experience in universities or healthcare settings. The appointees will play a pivotal role in ensuring the highest standards of quality across all aspects of its teaching, research, and clinically oriented activities, etc. They will promote academic collaboration both within and outside the Faculty and University and explore new strategic directions for the further development of the Department. Applicants who have responded to the previous advertisement (Ref.: 532420) need not re-apply. A highly competitive salary commensurate with qualifications and experience will be offered, in addition to annual leave and medical benefits. At current rates, salaries tax does not exceed 15% of gross income. The appointment will attract a contract-end gratuity and University contribution to a retirement benefits scheme, totalling up to 15% of basic salary. A monthly cash allowance will be offered to the successful candidate. Housing benefits will also be provided as applicable. The University only accepts online application for the above posts. Applicants should apply online, upload an up-to-date C.V. and provide the contact information of at least 3 referees. Review of applications will start from May 4, 2026 and continue until June 30, 2026, or until the posts are filled, whichever is earlier.

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 deliver on an industry innovation research project where you will be part of the research team to develop/produce/investigate a web-based Ship Simulation and Optimisation Software Platform. Key Responsibilities Participate in and manage the research project with Principal Investigator (PI), Co-PI and the research team members to ensure all project deliverables are met. Undertake these responsibilities in the project: i. Develop naval architecure calculation and ship design tools based on analytical or empirical methods, i.e., stability calculation, resistance and propulsion estimation, weight estimation, etc. ii. Develop a practical parametric model framework for ship and system design. iii. Carry out naval architecture calculations, i.e., stability, resistance, hydrodynamic analysis, etc. iv. Carry out ship hydrodynamic and CFD simulations. Coordinate procurement and liaison with vendors/suppliers. Work independently, as well as within a team, to ensure proper operation and maintenance of equipment. Job Requirements Have relevant competence in the areas of naval architecture and ship hydrodynamics. Have a degree in Naval Architecture / Marine Engineering / Ocean Engineering / Other Relevant Engineering Degree. Possessing a Master’s or PhD degree will be advantageous. Experience in any programming language will be advantageous. Experience in marine hydrodynamics will be advantageous. Key Competencies Able to develop naval architecture calculation and ship design tools Able to carry out ship hydrodynamic simulations Able to build and maintain strong working relationships with people within and external to the university. Self-directed learner who believes in continuous learning and development Proficient in technical writing and presentation Possess strong analytical and critical thinking skills Show strong initiative and take ownership of work

Role Overview 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 SIT Centre for Intelligent Robotics is a strategic capability centre under RoboPrecinct@Punggol Digital District (PDD), responsible for developing and maintaining the core applied robotics and embodied AI capabilities required for precinct-level deployment of robotic systems. The centre is seeking a Robotics Engineer. This role is application-driven and system-oriented, focusing on the implementation, adaptation, and evaluation of state-of-the-art robotics algorithms on real robotic platforms. The successful candidate will work closely with physical robots and simulation environments to translate recent advances in learning-based robotics into robust, deployable systems. Key Responsibilities Implement, adapt, and evaluate state-of-the-art learning-based methods for robotic perception, decision-making, navigation, and manipulation. Apply reinforcement learning, imitation learning, and other skill learning frameworks to practical robotic applications. Integrate learning-based robot skills with full robot software stacks in ROS / ROS 2 environments. Develop and maintain perception and state representation pipelines using RGB-D and 3D sensing. Conduct simulation-to-real (Sim2Real) workflows, including data collection, model training, deployment, and testing on physical robots. Support system-level experimentation, benchmarking, and iterative improvement of embodied AI applications. 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 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 field. Hands-on experience with deep learning frameworks such as PyTorch or TensorFlow. Working knowledge of reinforcement learning, imitation learning, or learning-based control concepts. Familiarity with robotics simulation tools such as Gazebo, Isaac Lab, or MuJoCo. Practical experience with ROS or ROS 2 for real-robot software integration. Proficiency in Python and C++, with experience developing and maintaining production-level code. At least 2 years of experience in robotics research or industry projects. Preferred Skillsets (Advantageous) Experience working with mobile manipulators, humanoid robots, or quadruped robots. Exposure to motion planning, control frameworks, or whole-body control systems. Experience with real-world robot experimentation and deployment. Experience with embodied AI and robot manipulation benchmarking platforms such as LIBERO, ManiSkill, or RLBench is highly desirable. Knowledge of GPU architectures, GPU cloud computing services, and strong familiarity with Linux operating systems. Knowledge of BIM, universal scene description and scene composition Knowledge of physics and simulation parameters, as well as sensor simulation pipeline.