Nueva Ecija University of Science and Technology (NEUST)

Join a unique British University in China. The University of Nottingham Ningbo China (UNNC) was the first Sino-foreign university to open its doors in China. This award winning campus offering a UK style education has grown to establish a student body of over 10,000 in just 21 years. It is looking for ambitious, talented academics with a passion for teaching as well as research flair to join its team of science and engineering experts. UNNC is part of the University of Nottingham’s Global University, and offers unique teaching and research opportunities in a highly dynamic economy. Applications are invited for the above post in the Electrical and Electronic Engineering (EEE) Department. The department delivers an undergraduate programme that is jointly accredited across the Nottingham campuses in the United Kingdom, Malaysia and China. It is expected that the successful candidate will support excellence in teaching in the Department and across the three campuses, while developing an internationally recognised research programme. Candidates must have a PhD or equivalent and post-doctoral academic research experience in a field related to electrical and electronic engineering. We are particularly interested in candidates with expertise in communications or photonics technologies; although excellent candidates in any research area with the ability to teach across a range of topics in our undergraduate curriculum will be considered. It is required that the candidate has strong academic experience and evidence of strong track record in his or her area of research. The appointment will be offered to the best qualified candidate based on their track record relative to their experience with the position being offered at either the Assistant or Associate Professor level. The successful candidate will be expected to lead and deliver individual and collaborative research and teaching in the area of electrical and electronic engineering, particularly on VLSI/Embedded System and contribute to the direction of research programmes in the Department of Electrical and Electronic Engineering. The role will be responsible for generating new intellectual understanding/knowledge through the application of knowledge and for developing ideas for application of research and teaching outcomes. The post holder will develop new concepts and ideas and will be expected, where appropriate, to develop and win support for innovative research and/or teaching development proposals and funding bids. The post holder will make a significant contribution to their academic unit via leadership and/or administrative management and/or co-ordination of specific initiatives. Salary will be within the range of 635,038 RMB to 780,622 RMB (Associate Professor) or RMB 450,190 to RMB 592,815 (Assistant Professor) per annum, depending on qualifications and experience (salary progression beyond this is subject to performance). In addition, an attractive package including employment support allowance, schooling and insurance will be provided for international appointments. The post will initially be offered on a fixed term contract with the University of Nottingham Ningbo China for a period of up to 5 years with effect from January 2026 or thereafter as soon as possible. This contract may be extended by mutual agreement, subject to revised terms and conditions. Informal enquiries may be addressed to: Dr C.F. Kwong, Department Head of Electrical and Electronic Engineering, email: chiew-foong.kwong@nottingham.edu.cn. Please note that applications sent directly to this email address will not be accepted. Interviews will take place in Ningbo, China, if feasible – virtual interviews may also held. Please be advised that normally your references will be contacted prior to the interview. For more details and/or to apply on-line please access: https://jobs.nottingham.edu.cn/job/184348/  If you are unable to apply on-line please contact the Human Resources Department, Tel: 86 574 8818 000 (Ext. 8404), Email: Job@nottingham.edu.cn. 

Ref.: 534052 Work type: Full-time Department: Restorative Dental Sciences of the Faculty of Dentistry (08026) Categories: Teaching Staff ​Applications are invited for appointment as Instructor in Dental Technology in the Faculty of Dentistry (Ref.: 534052), to commence as soon as possible, on a three-year fixed-term basis, with the possibility of renewal subject to satisfactory performance and funding availability.  Applicants should possess at least two Advanced Certificates in Dental Technology or equivalent, or a University degree in Dental Technology or equivalent. He/She should also have wide experience in Dental Technology, preferably with comprehensive skills in Prosthodontic, Orthodontic, and Digital Dental Technology (such as orthodontic appliances, virtual models, digital set-up, CAD/CAM and 3D printing technologies). Recent experience in teaching Dental Technology and a demonstrable interest in research and development in the field would be advantageous. The appointee will teach undergraduate and postgraduate students, participate in patient care and technique development, and contribute to administrative duties. Information about the Faculty can be obtained at http://facdent.hku.hk/. For general queries about the post, please contact Professor E.H.N. Pow, Division Chief of Restorative Dental Sciences in the Faculty of Dentistry at ehnpow@hku.hk. For further information about the duties of the post, please contact Mr. K.Y. Lai at kinglai@hku.hk. 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.  Housing benefits will also be provided as applicable. The University only accepts online applications for the above post. Applicants should apply online and upload an up-to-date C.V. Closes February 2, 2026. 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