Urdaneta City University

Research Assistant Professor in the Department of Pathology and the State Key Laboratory of Liver Research Ref.: 535085 Work type: Full-time Department: Department of Pathology, School of Clinical Medicine (21200) Categories: Senior Research Staff & Post-doctoral Fellow Applications are invited for appointment as Research Assistant Professor (RAP) in the Department of Pathology and the State Key Laboratory of Liver Research (Ref.: 535085), to commence as soon as possible, on a three-year fixed-term basis, with the possibility of renewal. Applicants should possess a Ph.D. degree in cancer biology or molecular biology, and in-depth experience as demonstrated by a relevant strong track record. Research experience in molecular cancer biology is required and experience with different animal models will be an advantage. Applicants should have a strong interest in translational research, the ability to work independently as well as in a team, and the ability to contribute intellectually to research development. The appointee will work in a multi-disciplinary group and investigate the molecular mechanism of liver cancer using cutting-edge strategies. The appointee will develop research programs independently, write scientific publications, grant proposals and reports, and supervise junior research staff and students. More information of the lab can be obtained in www.inglab.hku.hk or https://skllr.med.hku.hk/. Enquiries about the duties of the post should be sent to Professor Irene Ng at iolng@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. The University only accepts online applications 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 June 15, 2026, or until the post is filled, whichever is earlier. Advertised:Apr 24, 2026 (HK Time) Applications close:Jun 15, 2026 (HK Time)

Department: IT Services Vacancy ID: 041003 Closing Date: 07-May-2026 Maynooth University wishes to appoint a User Support Advisor (Microsoft 365 Support) on a full-time permanent basis. This appointment at AOII Grade will report to the User Support Manager and be part of the User Support Team within IT Services. The purpose of this role is to provide support, guidance and consultancy to help users effectively utilise the full range of Microsoft 365 tools and platform services. The role focuses on resolving user issues, improving digital confidence, and enabling staff to work productively and collaboratively across the organisation. By supporting day‑to‑day queries, promoting best practices, and helping users adopt new features, the role ensures that individuals can make the most of Microsoft 365 applications while maintaining a smooth and positive technology experience. The ideal candidate will have a strong ICT capability with deep expertise across Microsoft 365 with advanced proficiency in collaboration and productivity applications. They will be familiar with administration portals, and core services such as Exchange Online, SharePoint Online, Teams, OneDrive, Entra ID, and Intune. The successful candidate will be skilled in supporting users and advanced troubleshooting. They will be familiar with Microsoft 365 compliance and data management practices. They will be a strong collaborator with excellent interpersonal and communication skills. Salary: Administrative Officer II: €46,918 – €66,464 p.a. (9 points) Appointments will be made in accordance with public sector pay provisions. Closing Date: 23:30hrs (local Irish time) on Thursday, 7th of May 2026. Applications must be submitted by the closing date and time specified above. Any applications which are still in progress at the closing time on the specified closing date will be cancelled automatically by the system. Late applications will not be accepted. Maynooth University is an equal opportunities employer The position is subject to the Statutes of the University

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.