University of Technology and Applied Sciences - Muscat

Aalto University is where science and art meet technology and business. We shape a sustainable future by making research breakthroughs in and across our disciplines, sparking the game changers of tomorrow and creating novel solutions to major global challenges. Our community is made up of 16 000 students and 5 200 employees, including 446 professors. Our campus is in Espoo, Greater Helsinki, Finland.  Diversity is part of who we are, and we actively work to ensure our community’s diversity and inclusiveness. This is why we warmly encourage qualified candidates from all backgrounds to join our community. Call for Proposals: Two Postdoctoral Positions in Quantum Technology The Finnish Ministry of Education and Culture has announced additional support for national doctoral education pilot in quantum technology (QDOC) aimed at postdoc recruitments. The focus is on supporting the training and supervision of the 90 doctoral students who are currently enrolled under QDOC across Finland. QDOC team invites applications for two postdoctoral positions that combines research with the development and delivery of a course or training module aimed at QDOC students nationally. The duration for each position is one year, with the possibility of extension for an additional year. While the positions are formally hosted at Aalto University, the employee may, at their own discretion, pursue a visitor agreement with a QDOC host university, subject to agreement by Aalto University and the host university of the visit. Applicants should include a brief plan for potential visits in their application. We are open to research backgrounds in both academic and industrial environments. Your role and goals The postdoc must develop and deliver a course or training activity equivalent to 5 ECTS credits, targeted at QDOC students nationally, during the funding period. The course or activity focus may be technical (e.g. quantum science and technology, methods etc.) or general (e.g. scientific communication, supervision, entrepreneurship etc.). Co-supervision of QDOC students within the funding period is considered an advantage. We expect the candidates to have: Completed a PhD degree in a field complementary to the goals of QDOC. The candidate must show evidence of good written and oral communication skills in English. What we offer The positions are hosted at Aalto University under full-time employment agreement. The postdoc contracts will initially be made for 1 year. Employees could work remotely according to Aalto University’s remote work policy. Aalto University follows the salary system of Finnish universities. The salary ranges for a postdoc from 4138 € to 4549 € per month, depending on previous experience. The contract includes Aalto University occupational healthcare. Join us! The deadline for applications is 10.05.2026. To apply for the position, please submit your application including the attachments mentioned below as one single PDF document (max 2 pages) in English through our online recruitment system by clicking “Apply now!” button in our web page. Brief CV of applicant and research focus (max 1 page). Course or training activity concept with a short description of its contents and format (max 1 page). Role of applicant in co-supervision of QDOC students (if any). Please note: Aalto University’s employees should apply for the position via our internal HR system Workday (Internal Jobs) by using their existing Workday user account (not via the external webpage for open positions). If you are a student or visitor at Aalto University, please apply with your personal email address (not aalto.fi) via Aalto University open positions For more information about the role, please contact QDOC Director Prof. Adam Foster adam.foster@aalto.fi and Finnish Quantum Flagship Manager Dr. Mahdi Moghaddam mahdi.moghaddam@aalto.fi. For additional information on the application process contact Minni Forss, HR Advisor minni.forss@aalto.fi. We will go through applications, and we may invite suitable candidates to interview already during the application period. We aim for a prompt evaluation process, with both positions expected to begin on 01.06.2026. More about Aalto University: Aalto.fi youtube.com/user/aaltouniversity linkedin.com/school/aalto-university/ www.facebook.com/aaltouniversity instagram.com/aaltouniversity To view information about Workday Accessibility, please click here. Please see more of our Open Positions here.

The University of Southampton is one of the UK’s leading universities, with an extensive, diverse programme of world-class research and a creative, broad portfolio of taught programmes. Excellence in health & safety management and performance is critical to the continuing and developing success of our exceptional institution. We require a Radiation Protection / Health and Safety Officer to join our team of health & safety professionals. In addition to specialist radiation knowledge, you will need to be able to apply general expertise in health and safety to support the University activities. The role is responsible for development, implementation and review of the radiation protection management system that ensures the University maintains its compliance with the Ionising Radiations Regulations 2017 and the Environmental Permitting Regulations 2016 Main responsibilities: In liaison with the external RPA/RWA, to provide radiation protection advice and support to a wide range of research streams, and to promote continuous improvement of measures to reduce risk and exposure to ALARP. To manage the University’s Environmental Permits for radioactive waste disposal, and to provide oversight of its radiation protection management system. In liaison with the RWA, to provide advice on the best available techniques for management and disposal of radioactive waste to ensure compliance with the University’s Permits. To coordinate provision of dosimetry across the University. To carry out internal audits and inspections of the Faculties working with ionising radiations. To develop and deliver radiation protection training. To liaise with relevant regulators, including EA, HSE, CTSA and Fire Service. To provide general health and safety advice to academic schools and professional services within the University. Ideally, the successful candidate will have a proven track record of radiation protection and health and safety expertise, ideally in an education or research environment. Suitable applicants from other sectors will be considered. Applications from individuals working towards RPA/RWA accreditation will also be considered. NEBOSH General Certificate in Occupational Health & Safety (or equivalent) would be desirable, but is not a requirement.

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. This project focuses on federated causal inference in heterogeneous data environments, addressing the challenge of enabling trustworthy causal analysis across distributed datasets while preserving privacy. The successful candidate will be responsible for the end-to-end investigation of novel federated learning strategies for causal inference. The role will bridge rigorous theoretical work with hands-on algorithm design and development on real-world datasets. The core responsibility is to build and validate federated causal inference algorithms through simulations and live demonstrations. Key Responsibilities Participate in and manage the research project with Principal Investigator (PI) to ensure all project deliverables are met. Derivation of novel performance metrics for federated causal inference algorithms. Analysis of causal inference models in federated settings using synthetic and real-world datasets. Design and development of novel federated causal inference algorithms and associated software APIs. Validation of algorithms via simulations and live demonstrations. Job Requirements A Master's degree or higher in Computer Engineering, Computer Science, Data Science, Statistics, or equivalent. Strong theoretical background in statistics and machine learning. Knowledge of the basics of federated learning and causal inference is highly encouraged. Proven track record in research and development of machine learning algorithms. Proficiency in algorithm development using Python and ML frameworks such as PyTorch or TensorFlow. Key Competencies Work independently, as well as within a team, to ensure proper operation and maintenance of equipment. Able to build and maintain strong working relationships with people within and external to the university. Self-directed learner who believes in continuous learning and development. Proficient in technical writing and presentation. Possess strong analytical and critical thinking skills.