Universidad Metropolitana (Ecuador)

Ref.: 535079 Work type: Full-time Department: Centre on Contemporary China and the World (31110) Categories: Senior Research Staff & Post-doctoral Fellow Post-doctoral Fellow in the Centre on Contemporary China and the World (Ref.: 535079) Applications are invited for the appointment of Post-doctoral Fellow in the Centre on Contemporary China and the World at the University of Hong Kong, to commence from September 1, 2026, for 1-year temporary basis, with the possibility of renewal, subject to satisfactory performance and funding availability. Duties and Responsibilities CCCW is seeking a highly analytical and rigorously trained researcher to conduct original research and other tasks listed below: work on projects in the fields of (1) studies of ASEAN countries, (2) Chinese political leadership and governance, or (3) AI methods for social science related to the Centre’s priorities revise the doctoral dissertation for publication, if applicable design/refine research methodologies coordinate data collection and analysis support the organization of events assist in the preparation of reports perform other duties as assigned Requirements a Ph.D. degree in political science, international relations, economics, or a related discipline a demonstrated understanding of Chinese politics, economy, society, China-U.S. relations and broader international affairs, especially ASEAN countries, with record of publishing academic research papers knowledge of AI tools for social science research an excellent command of written and spoken English and Chinese good interpersonal, communication, organizational and problem-solving skills the ability to work independently and in a team self-motivated and responsible Successful candidates must be able to obtain the legal right to take up full-time employment and reside in Hong Kong during the Post-doctoral fellowship period. Visa and work authorization will be made possible for successful applicants through the Human Resources Office. What We Offer The appointment will commence from September 1, 2026, on a temporary basis for 1 year, with the possibility of renewal, subject to satisfactory performance and funding availability. 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 applications for the above post(s). Applicants should apply online at the University’s Careers site (https://jobs.hku.hk) and upload an up-to-date C.V., Personal statement in English describing research work experience and future research planning, and three names of references and their email addresses. Review of applications will start as soon as possible and continue until May 10, 2026, or until the post(s) is/are filled, whichever is earlier. The University is an equal opportunities employer and is committed to equality, ethics, inclusivity, diversity and transparency Advertised:Apr 23, 2026 (HK Time) Applications close:May 10, 2026 (HK Time)

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 skills that are relevant to industry demands while working on research projects in SIT.  About the DIGNIFIED programme The DIGNIFIED programme is dedicated to developing elderly-friendly, textured modified foods with desirable organoleptic and nutritional properties. Our mission is to enhance the quality of life for elderly individuals by creating innovative, nutritious, and visually appealing food products that cater to their specific dietary needs. Job Description:  We are seeking a highly motivated Research Engineer to join our team for a fixed-term project. The successful candidate will be responsible for developing and validating objective texture testing methods that can accurately categorize foods within the International Dysphagia Diet Standardisation Initiative (IDDSI) framework, with a specific focus on Level 5 (Minced & Moist). This role will involve designing custom test fixtures, conducting practical laboratory work, and performing data analysis to create a robust and reliable testing protocol. Key Responsbilities: Conduct a comprehensive literature review on food rheology, texture analysis, particle analysis, image analysis and the IDDSI framework. Design and execute experiments to develop new instrumental texture analysis methods suitable for IDDSI Level 5 foods. Validate new methods against existing standards and a sensory panel to ensure accuracy and clinical relevance. Collect, analyze, and interpret data from instrumental and sensory evaluations. Document all experimental procedures, findings, and analyses in technical reports and prepare presentations to industry stakeholders and manuscripts for publication in peer-reviewed journals. Collaborate with a research team, including food scientists, clinicians, and engineers, to ensure the developed methods are practical and clinically relevant. Job Requirements: A degree in Food Science, Food Engineering, Materials Science, or a related field. A Master's or Ph.D. in a related research field is advantageous. Experience with instrumental texture, image analysis and particle sizing techniques (e.g., texture analyzers, universal testing machines) is highly desirable. Strong analytical and problem-solving skills. Proficiency in material characterization techniques, such as stress-strain characterization. Proficiency in analysis software (e.g., Microsoft Excel, R, or other statistical software). Excellent written and verbal communication skills. Ability to work independently and as part of a team. Demonstrated commitment to strong research ethics and data integrity

About the University 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 Role We are seeking a highly motivated and talented Research Fellow to join an exciting industry-funded applied research project within the Infocomm Technology cluster at SIT. This project addresses the critical challenge of enabling ultra-reliable low-latency communications (URLLC) with priority-aware offloading for public safety services. The successful candidate will be responsible for the end-to-end investigation of novel edge-assisted computation offloading strategies that leverages edge intelligence. The role will bridge rigorous theoretical work with hands-on offloading algorithm design and development. The core responsibility is to build and validate these offloading strategies, complete with Python application programming interfaces (APIs), through rigorous simulations and proof-of-concept (PoC) trials. This position is ideal for a researcher with a passion for solving complex problems at the intersection of wireless communications, edge computing, and machine learning, and who is eager to translate theoretical insights into practical systems. Key Responsibilities Derive and analyse closed-form mathematical expressions for latency and offloading probabilities across edge-only, cloud-only, and edge-cloud computation offloading algorithms. Design and develop robust Python APIs for edge-only, cloud-only, and edge-cloud computation offloading algorithms. Set up network testbeds integrating hardware, software, and communication protocols to validate edge-only, cloud-only, and edge-cloud computation offloading algorithms. Conduct rigorous simulations and live PoC trials to ensure computation offloading algorithms meets URLLC targets for public safety services. Participate in and manage the research project with Principal Investigator (PI) to ensure all project deliverables are met. Job Requirements A Ph.D./Master’s degree in Computer Engineering, Communications Engineering, Computer Science, or a highly related discipline. A strong theoretical foundation and research background in wireless communications and edge computing. Strong publication track record in top-tier conferences and journals in the areas of wireless communications, IoT, or edge computing. Demonstrated proficiency in software API and algorithm development of edge intelligence algorithms using Python. Knowledge of machine learning or reinforcement learning techniques is highly advantageous. Experience with theoretical wireless network modelling, particularly stochastic geometry or queuing theory, is highly advantageous.