The Hong Kong Polytechnic University - Faculty of Business

At Adelaide University, we create the opportunities you need to achieve your ambitions – because when you thrive, we thrive. We are dedicated to ensuring the prosperity, wellbeing and cohesion of society by addressing educational inequality through our actions and through the success and impact of our students, staff and alumni. Partnered with the communities we serve, we conduct outstanding future-making research of scale and focus. The Research and Innovation Portfolio plays a pivotal role in driving world-class research that delivers global impact, strengthens our academic reputation and contributes to solving society’s most pressing challenges. It also champions inclusivity, commercialisation, and partnerships with industry, government, and global institutions. Reporting to the Deputy Vice Chancellor, Research and Innovation, the Pro Vice-Chancellor (PVC) Translational and International Research will provide strategic leadership and operational oversight of research commercialisation and business development activity to drive the University’s research engagement and translation activity. This role also brings the opportunity to develop, and with Colleges and Institutes, implement an international research strategy, aligned with external opportunity and the University Research Strategy. Positioning Adelaide as Australia’s premier for-purpose research university, the PVC will lead a multi-functional portfolio spanning Research Business Development, Research Commercialisation, translational research projects and international research acquisition. Working at the intersection of academia and industry, the successful candidate will lead the development of a more integrated, commercial and high-performing model and play a pivotal role in enabling research translation and enhancing outcomes for students, staff and partners. This senior role offers an outstanding opportunity for a credible and accomplished leader, from within or beyond higher education, with the capability to bridge academic and external environments while fine-tuning operations in a new University toward delivery of measurable outcomes including revenue growth. Candidates will bring strong strategic and commercial acumen, plus a track record of leading complex partnership, engagement, or enterprise activity. They will also demonstrate the judgement, presence and interpersonal style to shape teams and build trust with academic colleagues whilst engaging effectively and delivering outcomes with external partners. To learn more about this unique opportunity please contact our advising consultants Alun Parry, Vicky Garvey and Dr Margot Courtillat at Boyden on +61 2 9225 7400, or Margot.Courtillat@boyden.com Closing date: 20 July 2026

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. 

Salary: £35,608 - £43,482 per annum Contractual hours: 37 Basis: Full Time Package: Full details can be found here - https://www.ucb.ac.uk/about-us/work-for-us/rewards-and-benefits/ Job category/type: Academic, Construction, Engineering, Further Education Job reference: REQ000569 Attachments: attachmentCarpentry - JDPS - June 26.pdf Job description Do you have experience teaching carpentry in Further Education or are you an experienced Carpenter looking for a new challenge? We are looking to recruit a highly motivated Lecturer to join our growing team. You will want to pass on your skills to the next generation and will need to have relevant experience in construction. We welcome applications for part-time or full-time contracts. You will work with Senior Lecturers and the Head of Department to ensure our delivery is world class and that we produce work-ready students for employment or career progression. The ideal candidate for this role will be committed to self-development and to keep up to date with industry innovation. Standard Information UCB is an equal opportunities employer. University College Birmingham is proud to be TEF rated Silver, with a Good Ofsted rating UCB has achieved the Investors in Diversity Bronze Award. You may need to obtain permission to work in the UK if you don’t already have the unrestricted right to work in any role. There are various types of visa which include the right to work. You can check if you need a UK visa using the Government’s online tool and find information about UK visa routes and the eligibility criteria that must be met for each route Work in the UK - GOV.UK (www.gov.uk). All staff are required to prove their right to work in the UK before they start work. All applicants for employment at the University will be expected to undertake an Enhanced Check with the Disclosure and Barring Service prior to commencement. All applicants for employment at the University will be expected to demonstrate an understanding of the principles of Safeguarding and the PREVENT agenda in the context of further and higher education.