University of Wolverhampton

The University of Surrey is a global community of ideas and people, dedicated to life-changing education and research. We are ambitious and have a bold vision - shaping ourselves into one of the best universities in the world - which we are achieving through the talents and endeavour of every employee. Our high-achieving Advancement team recently closed its first global campaign, and is now building on this success to drive even greater philanthropic impact. Our high-achieving Advancement team recently closed its first global fundraising campaign, and is now building on this success to drive even greater philanthropic impact. The Advancement team of 25 ambitious professionals work with our global community of 153,000 alumni in 185 countries delivering alumni engagement activities and securing donations to support research and students at the University. The role We are seeking an outstanding assistant to provide high-quality, professional administrative and PA support to the Director of Advancement and the Advancement Leadership Team. This is a key role for an organised, proactive and personable individual who takes pride in delivering a seamless service, enabling senior leaders to operate effectively and efficiently within an ambitious Advancement function. The University operates a hybrid working approach and this role will be a minimum of three days per week office-based with flexibility to attend campus more frequently when required. Part-time hours will be considered for the right candidate. About you If you are highly efficient, dependable and trustworthy, with excellent administrative skills and a naturally warm and professional manner, we would welcome your application. You will join a friendly and forward-looking team at the University of Surrey, working in a collaborative environment and contributing to work that directly supports students, research and the University’s global ambitions.  How to apply To apply, please upload a CV and cover letter outlining why you would be a suitable candidate for the role. Previous applicants need not apply. The University of Surrey reserves the right to close this vacancy early based on volume and calibre of applications. If you would like to discuss the role further, please contact Michelle Cruickshank, Senior Alumni Relations Manager m.cruickshank@surrey.ac.uk for an informal chat. In return we offer a generous pension, flexible working options including job share and blended home/campus working locations (dependent on work duties), access to world-class leisure facilities on campus, a range of travel schemes and supportive family friendly benefits including an excellent on-site nursery. Click here to find out more about the benefits we offer to support you. The University of Surrey is committed to providing an inclusive environment that offers equal opportunities for all. We place great value on diversity and are seeking to increase the diversity within our community. Therefore we particularly encourage applications from under-represented groups, such as people from Black, Asian and minority ethnic groups and people with disabilities. Further details Job Description

Department of Computer Science of Faculty of Science invites applications for a DOCTORAL RESEARCHER IN MACHINE-LEARNING, STATISTICS AND DATA-CENTRIC ENGINEERING starting from September 2026, or as agreed. The Doctoral Researcher will be offered a full-time contract for the maximum duration of 3 years (possibly extendable to 3.5-4 years). There will be a trial period of six months at the beginning of employment.  Position description The successful candidate will work within the research project “Advances in generalized Bayesian inference via differential-geometric methods” funded by the Research Council of Finland under the supervision of the Academy Research Fellow Marcelo Hartmann and Research Fellow Luu Hoang Phuc Hau (Nanyang Technological University). We have been developing computational algorithms and theory grounded in notions of information geometry and Riemannian geometry to enhance Bayesian statistical inference and machine-learning related methods. The successful deployment of statistical models and AI solutions relies heavily on the quality of underlying model assumptions and the learning algorithms they employ. The design of loss functions is therefore crucial in the process of model development to the specific tasks at hand. For instance, the Hyvärinen score matching principle has been widely applied in AI systems, particularly for tasks such as diffusion-based image generation. This project seeks to further develop and broaden the range of loss functions by incorporating concepts from differential geometry. Additionally, we leverage the theory of estimating functions to create optimal inference algorithms for the proposed loss functions based on its underlying Riemannian geometry, as well as for those previously introduced in the literature. These advancements hold significant potential for a wide range of applications, spanning scientific research and societal challenges at large. The primary research site is the Department of Computer Science at the University of Helsinki (UH), strong synergy also exists between researchers at the Department of Computer Science at Aalto University, supported by the flagship grant from the Research Council of Finland (RCF) for AI research, called the Finnish Center for Artificial Intelligence (FCAI). This project is further related to the European Laboratory for Learning and Intelligent Systems (ELLIS unit Helsinki and ELLIS Institute Finland). Both institutes aim to foster cutting-edge research and establish a globally recognized concentration of expertise in ML and Statistics. You will also have the chance to collaborate with researchers from University of Cambridge (UK), Technical University of Denmark, University of Warwick, Nanyang Technological University and Hamburg University of Technology. Please check our personal website (as hyperlinks in our names) for details and news. The Doctoral Researcher is expected to: advance the research project together with the project leader and conduct doctoral studies and research work leading to a completed PhD thesis within 4 years. Your work may also include teaching duties (at most 5% of annual working time). Requirements and eligibility criteria The doctoral researcher should have a Master's degree in Statistics, Mathematics or Computer Science (or a related field) with an emphasis on applied mathematics/statistics/machine-learning. Prior experience in the probabilistic machine-learning, neural-networks, statistical inference and data modelling is a bonus. Prior experience in some computer programming language is expected (Python, Julia, R, Matlab etc). Excellent communication skills in English, both verbal and written, are naturally expected. In addition, according to the system of the University of Helsinki, all doctoral researchers belong to a doctoral programme. The successful candidate should apply to Doctoral Programme in Science and obtain the study right within the trial period of six months of their employment contract. Please check the admission periods and eligibility criteria at https://www.helsinki.fi/en/admissions-and-education/apply-doctoral-programmes/how-apply-doctoral-programmes Salary and benefits The starting salary of the Doctoral Researcher will be ca. 2800 euros/month, depending on the appointees’ qualifications and experience. The salary will develop in accordance with the progress of studies. The University of Helsinki offers comprehensive services to its employees, including occupational health care and health insurance, sports facilities, and opportunities for professional development. The University provides support for internationally recruited employees with their transition to work and life in Finland. Finland and the Helsinki region possess top expertise in sciences in terms of a vibrant talent pool, leading research, strong support services and functioning collaboration networks Finland is a member of EU, has high quality free schooling (also in English), generous family benefits and healthcare, and has been ranked as the happiest country in the world for eight consecutive years. For more information about working at the University of Helsinki and living in Finland, please see https://www.helsinki.fi/en/about-us/careers. A diverse and equitable study and work culture is important to us. That is why we do our best to promote an inclusive university community. We encourage all qualified applicants from diverse backgrounds to apply for our positions. Click this link to read about accessibility and inclusivity at our university How to apply Please submit your application, which includes the following documents in English: A motivation letter describing why you are interested in this position and how you are qualified (max. 1 page) A curriculum vitae including a list of publications (if any). One example of a written analytical text (e.g. Master’s thesis). If the text is not solo-authored, detail your contribution to producing the text. The names and contact information of two referees, who are willing to provide reference letters upon request (optional). External applicants, please submit your application through the University of Helsinki’s recruitment system via the Apply Now button. Internal applicants, applicants who have a helsinki.fi username and a valid employment/grant/visitor contract at the University of Helsinki are requested to submit their application via the Employee login button. We are eager to fill this position as soon as possible and therefore encourage early applications. However, the absolute deadline for submitting applications is July 15th, 2026 (at 23:59 UTC +2). More information? For questions project and position related questions, please contact  Academy Research Fellow (PI) Marcelo Hartmann, marcelo.hartmann@helsinki.fi For more information on the PI and publications, see https://www.helsinki.fi/en/researchgroups/multi-source-probabilistic-inference With technical questions related to the recruitment system, please contact recruitment@helsinki.fi. *** fThe Department of Computer Science is a leading unit in Finland in its area and responsible for the teaching and research in computer science at the University of Helsinki. The main research fields at the department are artificial intelligence, big data frameworks, bioinformatics, data analysis, data science, discrete and machine learning algorithms, distributed, intelligent, and interactive systems, networks, security, and software and database systems. The department has extensive international collaboration with companies and universities. Within teaching, the department’s professors and staff are in charge of the Bachelor’s, Master’s, and Doctoral Programmes in Computer Science, as well as the separate master's Programme in Data Science, in which other departments also participate. 

Job Description SCHOOL OF CONTINUING EDUCATION CONTINUING AND PROFESSIONAL EDUCATION DIVISION (CPED) The School of Continuing Education, one of the seven Faculties/Schools of the University and a major provider of continuing and professional education in Hong Kong, offers a wide range of full-time and part-time programmes at the post-secondary, undergraduate and postgraduate levels for young learners and working adults. It also offers in-house training and short courses to meet the community needs and market demands. Operated on a self-financed basis, the School and its College of International Education currently employ about 400 full-time staff and 550 part-time instructors. The School invites applications for the following positions in the Continuing and Professional Education Division: Lecturer I / Lecturer II / Assistant Lecturer (Accounting) (25260775) Applicants should possess relevant teaching and/or professional experience in one or more of the following areas: Financial Accounting Management Accounting Financial Management Economics Statistics The appointee is required to (i) perform teaching duties in related disciplines; (ii) provide academic guidance to students; (iii) develop, coordinate curriculum and manage programmes; (iv) supervise projects; (v) coordinate with the part-time teaching staff; (vi) assist administrative work for the responsible programmes/courses such as admission interview, handling students’ enquiries and organising student activities. Requirements: Applicants should possess a higher degree, preferably at the doctoral level, in the relevant discipline, along with teaching experience. A master's degree may also be considered. Candidates must demonstrate dedication and commitment to teaching and education; meanwhile, research competence is a factor to be considered. Excellent communication skills and the ability to work effectively within a team are essential. Candidates with less experience will be considered for the post of Lecturer II or Assistant Lecturer. Reference salary range:  Lecturer I: HK$51,000 - HK$86,000 Lecturer II: HK$38,000 - HK$53,000 Assistant Lecturer: HK$30,000 - HK$39,000 The appointee will mainly work at the Shek Mun (Shatin) campus. The initial appointment will be offered on a fixed-term contract ending in August 2027. Re-appointment thereafter will be subject to mutual agreement and availability of funding. Rank and salary will be commensurate with qualifications and experience. Application Procedure: Applicants are invited to submit their applications at the HKBU e-Recruitment System. Those who are not invited for interview 4 months after submission of application may consider their applications unsuccessful. Details of the University's Personal Information Collection Statement can be found at https://hro.hkbu.edu.hk/en/worklife-at-hkbu/employee-favourable-environment.html#privacy-policy. The University reserves the right not to make an appointment for the post advertised, and the appointment will be made according to the terms and conditions applicable at the time of offer. Review of applications is ongoing until the position is filled.