University of the Andes, Colombia

Department: Admissions Office Vacancy ID: 040703 Closing Date: 26-Apr-2026 Maynooth University is committed to a strategy in which the primary University goals of excellent research and scholarship and outstanding education are interlinked and equally valued. We are seeking a Student Recruitment Officer (permanent) to join the Admissions and Student Recruitment Office. This role is central to promoting the University to prospective students and supporting the wider Admissions and Student Recruitment function. A Student Recruitment Officer will foster meaningful connections with prospective students and their influencers, ensuring a welcoming, informative, and supportive experience. The post-holder will work collaboratively across the University and with external stakeholders, including guidance counsellors, teachers, school leaders, Colleges of Further Education, parents, and colleagues across academic and administrative departments. The Student Recruitment Officer position is ideal for someone with strong organisational, communication, and event management skills, who are proactive, flexible, and committed to delivering excellent service to prospective students. Applicants should note that there will be a requirement to to travel nationwide and work outside normal office hours (occasionally at short notice) including weekends. The post holder will report to the Director of Admissions or their nominee. Salary: Administrative Officer II (2026): €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 Sunday, 26th April 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

The Health and Social Sciences Cluster at SIT has been at the forefront of allied health education and research, offering a suite of allied health programmes and two nursing programmes. As a young university, we foster an academic environment that seamlessly integrates teaching, applied research and clinical practice. We offer competitive remuneration, generous employment benefits, access to funding to undertake clinical research, and opportunities to inspire and nurture the next generation of skilled allied health and nursing professionals. About the Positions  We currently have positions for Lecturer/Senior Lecturer in the discipline of Podiatry. Applicants should meet all the criteria below: (a)at least a Podiatry/Podiatric Medicine pre-professional degree and a Master's/post-professional specialisation qualification from reputable universities;(b)deep clinical experience in podiatry;(c)teaching and clinical education experience preferred. We will prioritise collegial and team-spirited candidates with an earned PhD in a related discipline from a reputable university, plus relevant work experience or experience of industry-linked applied research projects. Applications will be accepted until the positions are filled. All applications must be submitted electronically via the "Apply Now" button below. 

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.