University of Agder

Ref.: 534646 Work type: Full-time Department: The Hong Kong Jockey Club Centre for Suicide Research and Prevention (30002) Categories: Senior Research Staff & Post-doctoral Fellow Post-doctoral Fellow in the Hong Kong Jockey Club Centre for Suicide Research and Prevention within the Faculty of Social Sciences (Ref.: 534646) We now invite applications for the captioned post. Duties and Responsibilities Drive research activities towards defined goals and priorities within a specified timeline Perform advanced level of data analysis (quantitative and qualitative) Advance knowledge based on the data and disseminate it through peer-review journals or other means Draft proposals, reports and presentations relevant to the projects Liaise with project collaborators and partners Mentor junior research staff Support and perform other duties as assigned Requirements a Ph.D. degree in Psychology, Social Sciences, Social Work, Public Policy, Public Health or related disciplines A strong sense of self-motivation, responsibility, and work ethics Good analytical, communication, organizational and problem-solving skills The ability to multi-task and work on a tight schedule to meet project deadlines The ability to work well independently and collaboratively as a team The capacity to develop and pursue a coherent research agenda The ability to develop a body of high-quality publications in scholarly journals with global impact Proficiency in statistical software packages, including R and SPSS, for large and complex data analysis What We Offer The appointment will commence as soon as possible on a 1-year temporary basis, with the possibility of renewal subject to satisfactory performance. A highly competitive salary commensurate with qualifications and experience will be offered. Other benefits include annual leave, medical benefits and free access to on-campus gyms and libraries. How to Apply The University only accepts online application for the above post. Applicants should apply online and upload an up-to-date C.V. Review of applications will start as soon as possible and continue until March 31, 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

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

Ref.: 534618 Work type: Full-time Department: Department of Physics (25600) Categories: Senior Research Staff & Post-doctoral Fellow Post-doctoral Fellow in High-Energy Astrophysics in the Department of Physics Applications are invited for appointment as Post-doctoral Fellow in High-Energy Astrophysics in the Department of Physics (Ref.: 534618), to commence as soon as possible for two years, with the possibility of renewal subject to funding availability and satisfactory performance. Applicants should possess a Ph.D. degree in Physics or Astronomy. The appointee will work with Prof. Stephen C.Y. Ng to pursue research in areas related to neutron stars, pulsar wind nebulae, or supernova remnants. Applicants with experience analysing radio interferometer data are especially encouraged to apply. A highly competitive salary commensurate with qualifications and experience will be offered. Other benefits include annual leave, medical benefits, and free access to on-campus gyms and libraries. At current rates, salaries tax does not exceed 15% of gross income. The University only accepts online application for the above post. Applicants should apply online and upload an up-to-date C.V. (including a publication list), a cover letter, and a research statement. Applicants should also arrange three reference letters to be sent to Prof. Stephen Ng by e-mail (stephen_ng@hku.hk) directly. Review of applications will start as soon as possible and continue until April 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