Exeed College

Department: IT Services Vacancy ID: 041063 Closing Date: 04-May-2026 We are seeking to appoint a CRM Officer on a full-time, permanent basis, at Administrative Officer II Grade, within IT Services. The CRM Officer position will provide technical CRM services to university departments. The University has invested in strategically placed CRM Systems including those for student recruitment and admissions (Ellucian CRM Recruit), student engagement and success (TargetConnect) and communication and event management (Gecko Engage). The CRM Developer will initially focus on designing, developing, and implementing solutions within these CRM platforms to further enhance, optimize, automate, integrate and harmonize their services according to business needs and the Universities’ strategic objectives. Administrative Officer II (2026) Salary: €46,918– €66,363 p.a. (9 points) Appointments will be made in accordance with public sector pay provisions. Closing Date: 23:30hrs (local Irish time) on Monday, 4th 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

At the University of Vienna, almost 11,000 people work together on the big questions of the future. Approximately 7,700 of them are academic staff members. These are individuals who, with their curiosity and their continuous pursuit of excellence, engage in international cutting-edge research and teaching. With us, you will also find space to unfold your potential. We are looking for a/an ... Scientific project assistant predoctoral 37 Faculty of Business, Economics and Statistics Startdate: 01.06.2026 | Working hours: 30 | Collective bargaining agreement: §48 VwGr. B1 Grundstufe (praedoc) Reference no.: 5569 Explore and teach at the University of Vienna, where more than 7,500 academics thrive on curiosity in continuous exploration and help us better understand our world. Does this sound like you? Then join our accomplished team! Your personal sphere of influence: The research group Statistical Analysis and Inference (STAIN) (https://stain.univie.ac.at/) at the Department of Statistics and Operations Research (https://isor.univie.ac.at/), University of Vienna, is offering a PhD position in the area of Mathematical Statistics and Machine Learning, starting at the earliest possible date, and no later than September. The doctoral position is funded within the framework of a FWF project and is part of the DFG–FWF Research Unit 5381 (https://for5381.uni-freiburg.de/en/research-unit-5381/). The Research Unit offers a highly stimulating and collaborative research environment, including numerous scientific events, workshops, and joint activities, from which early‑career researchers benefit particularly strongly. Your future tasks: You actively participate in research and administration, which means: In collaboration with your advisor you will develop and complete your own PhD-project in the area of mathematical statistics or the theory of machine learning. We expect you to finalize your dissertation agreement (= project proposal) within 12-18 months and that you regularly participate in the PhD seminar. You get acquainted with a recent research area, formulate new and relevant mathematical problems and solve them independently under the supervision of your PhD advisor. You take on administrative tasks in research. You work on your own publications, academic articles and presentations. This is part of your personality: Completed Master's degree or diploma, in the field of statistics, mathematics or a closely related field (completed or about to be completed). A strong background in mathematical statistics and probability theory. Enthusiasm for abstract mathematical problems and strong tenacity and patience in solving them. Active interaction and discussion with the colleagues from the research group and the department. Programming skills. Didactic competences / experience with e-learning. Excellent command of written and spoken English (C1 Level). What we offer: The employment duration is 3 years. Initially limited to 1.5 years, the employment relationship is automatically extended to 3 years if the employer does not terminate it within the first 12 months by submitting a declaration of non-extension. With appropriate work progress, an extension to a total maximum of 4 years is possible. Work-life balance: Our employees enjoy flexible working hours and can partially work remotely. Inspiring working atmosphere: You are a part of an international academic team in a healthy and fair working environment. Good public transport connections: Your workplace is easily accessible by public transport. Internal further training & Coaching: Opportunity to deepen your skills on an ongoing basis. There are over 600 courses to choose from – free of charge. Fair salary: The basic salary of EUR 3.776,10 (on a full-time basis) increases if we can credit professional experience. Equal opportunities for all: We welcome every additional/new personality to the team! It is that easy to apply: With your scientific curriculum vitae. With a letter of intent outlining especially your previous experience with mathematical problem solving (max. 1 page). With your summary of research interests (max. 1 page) With contact details of at least two persons who agreed to provide reference letters upon request. Transcripts and Master Degree  /  Diploma (if available). Via our job portal/ Apply now -  button. If you have any questions, please contact: Johannes Moritz Jirak moritz.jirak@univie.ac.at We look forward to new personalities in our team! The University of Vienna has an anti-discriminatory employment policy and attaches great importance to equal opportunities, the advancement of women and diversity. We place particular emphasis on enhancing women’s representation among the academic and general university staff, particularly in leadership roles, and therefore expressly encourage qualified women to apply. Given equal qualifications, preference will be given to female candidates. University of Vienna. Space for personalities. Since 1365. Data protection ​Application deadline: 05/11/2026

Organisation: Cranfield University Faculty or Department: Faculty of Engineering and Applied Sciences Based at: Cranfield Campus, Cranfield, Bedfordshire Hours of work: 37 hours per week, normally worked Monday to Friday. Flexible working will be considered. Contract type: Fixed term contract Fixed Term Period: For 24 months Salary: Full time starting salary is normally in the range of £37,897 per annum Apply by: 18/05/2026 Role Description We welcome applications from passionate and skilled researchers to join our team in the Centre for Digital and Design Engineering, contributing to the EPSRC-funded TransiT project, focused on Digital Twinning Technologies for Transport Decarbonisation. About the Role We are looking for a Research Fellow to help develop new digital tools, including digital models, shadows and twins, that reduce carbon emissions in transport. Working with a wide range of experts from universities and industries across the UK, you will help create a “digital twinning” system that links air and road systems to support cleaner, more efficient and cost-effective logistics. The role involves building computer simulations and digital infrastructure using right-time data to test low-carbon and green technologies, and to provide evidence to guide future transport and energy planning. This position offers the chance to make a real contribution to the UK’s goal of achieving net-zero emissions by 2050. About You Applicants should have a doctorate degree or equivalent (PhD/EngD) in Engineering, Manufacturing, Transport, Computer Science, Data Science, Sustainability, or a closely related subject, or be close to completing their qualification. They should have experience in systems engineering, simulation, digital modelling, machine learning, artificial intelligence, or digital twin (model, shadow, twin) technologies, with an understanding of how these can be applied to transport or logistics systems. Strong technical and analytical skills are required, including experience using simulation or programming tools such as MATLAB, Simulink, MATSim, AnyLogic, or Python. Applicants should also have a good knowledge of decarbonisation and sustainability principles in transport, energy systems or manufacturing. Excellent communication, teamwork, and time management skills are essential, along with the ability to manage research activities and present finding clearly. Experience working on collaborative research projects with both academic and industry partners, or through funded research programmes, would be an advantage. About Us As a specialist postgraduate university, Cranfield’s world-class expertise, large-scale facilities and unrivalled industry partnerships are creating leaders in technology and management globally. Learn more about Cranfield and our unique impact here. Cranfield’s Manufacturing, Materials and Design theme is driving innovation towards a sustainable manufacturing sector by 2050, focusing on smart, clean and green solutions across all industry sectors and supply chains. The theme integrates expertise in design, advanced manufacturing, materials technology and digital engineering to deliver impactful research and postgraduate education. Within this theme, the Centre for Digital and Design Engineering (CDDE) leads research in digital engineering, simulation, artificial intelligence and digital twinning, developing tools and methods that enhance the design, manufacture and operation of complex systems. CDDE works closely with industry and government to create digital solutions that support the transition to low-carbon, resilient and efficient transport and manufacturing systems. Our Values and Commitments Our shared, stated values help to define who we are and underpin everything we do: Ambition; Impact; Respect; and Community. Find out more here. We aim to create and maintain a culture in which everyone can work and study together and realise their full potential. We are a Disability Confident Employer and proud members of the Stonewall Diversity Champions Programme. We are committed to actively exploring flexible working options for each role and have been ranked in the Top 30 family friendly employers in the UK by the charity Working Families. Find out more about our key commitments to Equality, Diversity and Inclusion and Flexible Working here. Working Arrangements Collaborating and connecting are integral to so much of what we do. Our Working Arrangements Framework provides many staff with the opportunity to flexibly combine on-site and remote working, where job roles allow, balancing the needs of our community of staff, students, clients and partners. How to apply For an informal discussion about this opportunity, please contact Dr Maryam Farsi, Senior Lecturer in Engineering Optimisation, on (T): +44 (0) 1234 754647 or (E): maryam.farsi@cranfield.ac.uk Please do not hesitate to contact us for further details on (E): peoplerecruitment@cranfield.ac.uk. Please quote reference number 5293. Closing date for receipt of applications: 18 May 2026 Please note that we reserve the right to close this advert prior to the stated closing date should we receive sufficient numbers of applications. Therefore, we would encourage you to complete and submit your application as soon as possible.