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Director, Office for Research
Griffith University
Australia, Mount Nathan
Griffith University
Australia, Mount Nathan
Brisbane South (Nathan), Queensland Australia Full-time Every institution values excellence. What matters most is why. Griffith was created to be a different type of university. You’ll find we’re about leading research, academic excellence, and the transformative power of education. But what sets us apart is why those things matter and how you’ll achieve them. Why? Griffith brings together exceptional minds like yours from across the globe and from all walks of life. Here, we do incredible work, questioning and challenging, always in the pursuit of excellence. Job Description Griffith University is recognised as a comprehensive research-intensive university, deploying a transformational research vision in recent years that has delivered an exponential uplift in research metrics and redefined how we support research. With our recently published Research and Innovation Plan (2025-2030) we are now poised to enter a new era – one where we scale our efforts, deepen our impact and lead with purpose; it is an exciting time to be a research leader at Griffith University. The Office for Research drives the University’s research agenda by providing end-to-end research management support across the research lifecycle. Griffith’s Office for Research has tactically combined research functions that are often separated in other universities, to streamline our end-to-end systems and processes, providing a fully integrated model of embedded and comprehensive research support. As such, the Director’s role is pivotal in its influence of the University’s research success. Collaborating with other business units within the Deputy Vice Chancellor (Research) portfolio, including Griffith Enterprise and Griffith Graduate Research School, as well as other central units and academic groups, the Director reports directly to the Deputy Vice Chancellor (Research). This key position provides strategic advice and risk management on all research, research funding and research policy matters affecting the overall research performance of the University. The role will lead and direct the overall operations of the Office for Research to support the University’s research performance targets and enhance its research profile with its principal external and internal stakeholders at state, national and international levels. About you As a key member of the leadership team and advisor to the Deputy Vice Chancellor (Research), we seek a leader who has the vision and ambition to help us deliver on our new Research and Innovation trajectory, and who can see the opportunities available, and respond quickly to leverage them. This role is about leading and delivering more than Griffith has already achieved, whilst remaining cognisant of the governance and compliance framework in which research excellence must thrive. The next Director of Griffith’s Office for Research can demonstrate their success in establishing systems, policies and procedures underpinning the delivery of client-focussed services that enhance institutional performance. The successful candidate will be a high achieving individual with strategic and dynamic leadership experience, driving performance at the nexus of private and public sectors. Strong interpersonal and relational skills, an inherently collaborative approach, the ability to think big, and to address challenges in the context of an ever-evolving governance and funding environment will be key attributes for success. What we can offer This is a five-year fixed term, full-time position primarily based at Griffith University Brisbane South (Nathan). As Griffith is a multi-site University you may be required to work across other locations. Griffith University’s campuses are located on the lands of the Yugarabul, Yuggera, Jagera, Turrbal, Yugambeh and Kombumerri peoples. Salary Range An attractive salary package will be negotiated. Additional information Why Griffith? As a values-led organisation, at Griffith University, we've worked hard to create a dynamic and strong organisational culture. We offer: Wide range of Learning and Development opportunities Mix of on campus and work from home options available and a supportive work environment Salary packaging options and corporate health discounts Generous leave entitlements including paid parental leave and leave loading Support with future learning opportunities through our educational staff assistance scheme Health Safety and Wellbeing initiatives – on campus Gym facilities How to apply At Griffith, we’re committed to providing a safe and inclusive environment for all - whoever you are and wherever you’re from. If you require any accommodations, we welcome you to let us know so we can work with you to participate fully in our recruitment experience. Griffith University values diversity, inclusion and flexibility and we encourage Aboriginal and Torres Strait Islander, and people of all backgrounds to apply. For more information please visit our Equity, Diversity and Inclusion page. Our University is committed to fostering a safe, respectful and inclusive community for all. In alignment with the National Higher Education Code to Prevent and Respond to Gender-based Violence (2025), Griffith University includes a declaration as part of the recruitment journey to uphold the values and standards of our community. Griffith University also maintains a strict zero-tolerance policy against all forms of modern slavery. For more information, please refer to Griffith’s Modern Slavery Policy. Please submit your application online and ensure it includes the following: A covering letter stating how you can fulfil the responsibilities of the role (please refer to the About you section above and the position description) Current curriculum vitae/resume including full contact details Applicants must have unrestricted working rights. Visa sponsorship is not available for this position. Successful candidates may be subject to a criminal history check. For further information specifically about this role, please contact the Deputy Vice Chancellor (Research), Professor Lee Smith, at dvcr@griffith.edu.au. For further application and recruitment advice, please contact Theresa Burke, Talent Acquisition Partner on t.burke@griffith.edu.au. Closing date: Monday, 22 June 2026 at 5pm. All applications must be submitted online. Please allow at least 1 – 2 weeks from the closing date to expect an application update.
Salary
Competitive
Posted
1 Jun 2026
Dean, Saïd Business School
University of Oxford
United Kingdom, Oxford
University of Oxford
United Kingdom, Oxford
The University of Oxford’s Saïd Business School is seeking an outstanding academic leader to serve as its next Dean, leading a globally recognised business school distinguished by its international outlook, entrepreneurial spirit, academic excellence, and commitment to addressing complex global challenges through research, education, and engagement. The Dean will provide strategic and academic leadership across all aspects of the School’s activities, working collaboratively with colleagues across the collegiate University and beyond. Alongside advancing research excellence, educational innovation, and external engagement, the Dean will play a central role in fostering an inclusive, supportive, and high-performing culture. The successful candidate will demonstrate a deeply people-centred approach to leadership, with the ability to build trust, empower others, develop talent, and create an environment in which faculty, professional services staff, and students can thrive. The successful candidate will be effective in building trusted relationships internally and externally, and in bringing people together around a shared sense of purpose and ambition. The successful candidate will bring intellectual credibility, strategic judgement, and outstanding leadership skills, together with the ability to inspire and unite a diverse community. They will be an effective ambassador for the School, building strong relationships within the School, across Oxford, and with alumni, donors, policymakers, industry leaders, and partners across the globe. This is a rare opportunity to lead one of the world’s most distinctive business schools at a time of profound change, and to shape the contribution Oxford Saïd can make to business, policy, and society in the years ahead. For further details and information on how to apply, please visit www.odgers.com/96125
Salary
Competitive
Posted
1 Jun 2026
Lecturer / Associate Professor / Professor in Logistics Information Systems
Hainan Bielefeld University Of Applied Sciences (Biuh)
China
Hainan Bielefeld University Of Applied Sciences (Biuh)
China
The Hainan Bielefeld University of Applied Sciences (BiUH) is the first international independent university in the Hainan Free Trade Port. Our approach combines theory and practice following the renowned "Work-Integrated University-Industry Collaborative Talent Training Model." We offer cutting-edge programs in high-demand fields: Digital Technologies, Computer Science, Logistics Engineering, Industrial Engineering, Mechatronics and Automation, Software Engineering and Business Administration. Our students benefit from small classes, English-language instruction with accompanying German courses, and intensive learning experiences. The focus is on mastering real-world professional challenges, enabling students to apply their knowledge immediately and preparing them optimally for the global job market. We combine international teaching standards with the unique opportunities that Hainan offers. BiUH is located in the Yangpu Economic Zone in Danzhou, a historic coastal city with direct high-speed rail connections to Haikou and Sanya. We invite passionate educators and researchers at all career stages, from early-career lecturers to established professors, to join our team. Both full-time and part-time positions are available for those committed to application-oriented education. Job Responsibilities Teach and assess at least 3 courses in the following subjects: Business Process Modelling and IT Systems Logistics IT Systems Procurement, Production and Logistics Supply Chain Management Digital Factory Planning and Simulation Develop course materials and curricula aligned with international standards and industry needs. Supervise student projects and internships in business process optimization, IT system implementation, and digital transformation. Engage in applied research and publish in peer-reviewed journals. Collaborate with industry partners for consulting projects and practical student training. Job Qualifications Master's degree or above in Information Systems, Business Administration, Logistics and Supply Chain Management, Industrial Engineering or closely related field. Strong foundation in business process modelling and IT systems. Strong foundation in system analysis, data management, and business process optimization principles. Industry experience in IT consulting, ERP implementation, or business process optimization strongly preferred. Ability to work effectively in an international and multicultural environment. Excellent communication skills in English; Chinese language skills are a plus. Expected Onboarding Time Autumn Semester 2026 (August 2026) Salary and Benefits Competitive Salary in the Market (13th Month Salary) Allowance: Travel Allowance / Phone Allowance / High Temperature Allowance, Etc. 5 Types of Social Insurance and 1 Housing Provident Fund Commercial insurance Transitional Apartments Arrangement Working environment that is open to the world and strongly oriented towards sustainability, diversity and internationality How to apply Please prepare the following documents: Current English CV (including full publication list) Cover Letter (addressed to the President) 2 Reference Letters Teaching Qualification Documents, Qualifications (if available) Documents certifying the professor's (if available) Academic Degree Certificates Please import all files into one PDF Please name the PDF as "Position - Your Name" Please send all files to recruitment@hibiuh.edu.cn
Salary
Competitive Salary in the Market
Posted
1 Jun 2026
Postdoctoral Researcher / Doctoral Researcher Positions in Machine Learning
Aalto University
Finland
Aalto University
Finland
Several Postdoctoral researcher and 1-2 doctoral researcher positions in machine learning in Kaski Lab, ELLIS Institute Finland and Manchester Centre for AI Fundamentals Samuel Kaski’s two-part research lab in ELLIS Institute Finland (Probabilistic Machine Learning, Aalto University) and the Centre for AI Fundamentals in University of Manchester, is searching for postdocs and doctoral students to work on AI fundamentals in exciting projects. The work includes collaboration within ELLIS Institute Finland, the Finnish Center for Artificial Intelligence (FCAI), with the rest of ELLIS, and researchers from other fields. Samuel Kaski is Professor of Computer Science in Aalto University and Professor of AI in the University of Manchester. He is the Director of ELLIS Institute Finland and the Finnish Center for Artificial Intelligence. His research group develops machine learning principles and methods focusing on a few key topics, often working with researchers of other fields in new exciting applications (see currently available topics below). Topics You will join a team developing the next generation of probabilistic and collaborative AI. We study fundamental questions in machine learning, including uncertainty-aware and simulation-based inference, generative modeling, robustness under distribution shift, automatic experimental design, privacy-preserving learning, (inverse) reinforcement learning, computational rationality, and user modelling. Our goal is to develop principled AI methods that are reliable, adaptive, and scientifically useful. The research combines advances in ML foundations with real-world applications in domains such as scientific discovery, healthcare, and design or drugs, materials, systems. By bringing together expertise in machine learning, statistics, optimization, we tackle challenging interdisciplinary problems that cannot be solved by any single approach alone. Below, we outline the research topics for which we are currently seeking candidates. Multimodal foundation models Key words: multimodal learning, foundation models, human-aligned fine-tuning, fine-tuning for downstream tasks, test-time adaptation You will join a research team developing next-generation multimodal foundation models that can reason across text, images, video, and 3D molecular design and robotic environments. The research is conducted within an EU-funded European AI initiative ELLIOT. Our goal is to make these systems more grounded, adaptable, efficient, and aligned with human goals and feedback. The work combines fundamental advances in multimodal representation learning with practical questions of deploying large-scale AI systems in dynamic real-world settings. Depending on your interests, you may work on topics such as large-scale multimodal training, test-time adaptation under distribution shift, efficient model distillation and adaptation, retrieval-augmented learning, or alignment through human feedback, preference, and interaction. Out-of-Distribution Deployable Machine Learning Key words: out-of-distribution generalization, distribution shift, active learning, human-in-the-loop learning, probabilistic modelling, sequential experimental design, collaborative AI, decision support We develop machine learning methods that remain reliable when deployed outside their training conditions. A central challenge in modern AI is that real-world environments differ from the data that models were trained on, leading to failures caused by distribution shifts, hidden confounders, and incorrect assumptions. Our ERC AdG-funded research addresses these challenges by combining probabilistic machine learning, adaptive inference, and human-collaborative AI. Your work will focus on developing algorithms and frameworks that enable models to adapt to new environments, learn efficiently from limited feedback, and support human decision-making under uncertainty. Depending on your interests, the research may involve out-of-distribution generalization, domain adaptation, active learning, learning from expert feedback, sequential experimental design, collaborative AI systems, or probabilistic approaches to robust deployment. The project combines foundational ML research with opportunities to collaborate closely with leading application-domain experts and international research partners. Collaborative AI Key words: collaborative AI, human–AI interaction, decision support, human-in-the-loop learning, uncertainty-aware AI, interactive machine learning, computational rationality, AI-assisted discovery You will join a research team developing collaborative AI systems that work effectively with people in complex decision-making and problem-solving tasks. Our goal is to build AI methods that can interact naturally with users, reason under uncertainty, adapt to human preferences and expertise, and support reliable human decision-making. The research combines machine learning, probabilistic modelling, cognitive modelling, and interactive AI to develop systems that complement rather than replace human intelligence. You may work on topics such as human-in-the-loop learning, uncertainty-aware decision support, preference learning, adaptive interaction, AI-assisted scientific discovery, computational rationality, or collaborative reasoning between humans and AI systems. The work addresses both foundational questions in human-centered machine learning and practical challenges in deploying collaborative AI in real-world environments. The work offers opportunities to collaborate with leading international researchers and application-domain experts in areas including healthcare, sciences, and intelligent decision support. Fundamental and Applied Machine Learning Research Key words: machine learning, probabilistic modelling, generative AI, representation learning, optimization, trustworthy AI, adaptive systems, AI for science We are also looking for researchers interested in tackling ambitious open problems in machine learning beyond the themes listed above. Our group works on a broad range of topics spanning probabilistic modelling, generative AI, adaptive and interactive learning systems, trustworthy AI, and AI methods for scientific discovery and decision-making. We are particularly interested in research that combines strong methodological foundations with the potential for high real-world impact - and the impact can come at different time horizons. Depending on your background and interests, your work may involve developing new machine learning principles, scalable inference and optimization methods, robust and uncertainty-aware AI systems, generative models, representation learning methods, or novel applications of AI in science, healthcare, and intelligent systems. We encourage interdisciplinary research and collaboration across machine learning, statistics, cognitive science, and application domains. The position offers considerable freedom to shape research directions while contributing to a collaborative and internationally connected research environment. Your experience and ambitions We expect the candidates to have a solid background in the mathematics/statistics/computer science needed in machine learning, and hold or be close to getting a relevant doctoral degree for a postdoctoral researcher and a master degree for a doctoral student researcher. Previous experience in the application fields and cognitive science is an advantage. Capability of both independent work and teamwork, and excellent written and spoken English are necessary. We provide 1) RESEARCH ENVIRONMENT You will work in Professor Samuel Kaski’s research group in ELLIS Institute Finland (Probabilistic Machine Learning Group) or the UK (Centre for AI Fundamentals). We design collaborations as we go, according to what the research needs. Collaborators include but are not restricted to the other groups in ELLIS Institute Finland, the Finnish Center for Artificial Intelligence (FCAI), other sites of the European Laboratory for Learning and Intelligent Systems (ELLIS) and Centre for AI Fundamentals of the University of Manchester and a number of excellent researchers in other fields in our applications. 2) JOB DETAILS Postdoc positions are typically made for up to three years, with option for renewal; doctoral-student positions start with a two-year contract and continue with a second two-year contract after a check-point. Starting dates are flexible and all positions are negotiated on an individual basis. We are strongly committed to offering everyone an inclusive and non-discriminating working environment. We warmly welcome qualified candidates from all backgrounds to apply and particularly encourage applications from women and other groups underrepresented in the field. All our positions are fully funded and the salary is based on the Finnish universities’ pay scale. The starting salary depends on the level of the position and the previous experience and is typically starting from 4200€ for postdocs and 3100€ for doctoral students, increased as the experience grows. All employees have access to occupational health care services and are covered by the Finnish national health insurance system. Ready to apply? Submit your application through Aalto recruitment system Workday by the button below “apply now”. The deadline for applications is June 28 2026 at 23:59 Finnish time. You can either submit a separate application to the University of Manchester (the application link will be added in early June) if you want to be considered for both locations, or a single application if you want to be considered only for that specific location. Required attachments Cover letter (1–2 pages). CV List of publications (please do not attach full copies of publications) A transcript of doctoral study and earlier studies (especially for doctoral students) The degree certificate of your latest degree. If you don’t yet have a PhD degree for a postdoctoral researcher position or a Master degree for a doctoral student position, a plan of completion must be submitted. Contact details of two senior academics who can provide references. We will contact your referees if we need recommendation letters. All materials should be submitted in English in a PDF format. Note: You can upload max. five files to the recruitment system, each max. 5MB. Please note: Aalto University’s employees and visitors should apply for the position via our internal system Workday -> find jobs (not external aalto.fi webpage on open positions) by using their existing Workday user account. Contacts: Coordinator Fang Wang (fang.wang@aalto.fi) More Information We are part of ELLIS Institute Finland, which is a leading research environment building on Finland’s strong track record in machine learning research, including work at the Finnish Centre for Artificial Intelligence FCAI. ELLIS Institute Finland is part of the European ELLIS network and operates in close partnership with Finnish universities, RDI organizations, and industry, forming a vibrant AI and machine learning ecosystem. The Institute offers excellent computational resources - its own resources and through CSC, including access to the LUMI supercomputer and the European AI Factory, and is located in Otaniemi, Espoo, within a dynamic research and innovation hub. Aalto University is a community of bold thinkers where science and art meet technology and business. We are committed to identifying and solving grand societal challenges and building an innovative future. Aalto has six schools with 14 000 students and a staff of 5000, of which more than 400 are professors. Our main campus is located in Espoo, 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. The Department of Computer Science is an internationally-oriented community and home to world-class research in modern computer science, combining research on foundations and innovative applications. With over 40 professors and more than 450 employees from 50 countries, it is the largest department at Aalto University and the leading computer science research unit in northern Europe. Computer science research at Aalto University ranks high in several international surveys (7th in Europe and 1st in the Nordics (NTU 2023); and 88th worldwide in Times Higher Education subject ranking 2025). About Finland Finland is a great place for living with or without family – it is a safe, politically stable and well-organized Nordic society. Finland is consistently ranked high in quality of life and was just listed again as the happiest country in the world: World Happiness Report 2025: People are much kinder than we expect, research shows | The World Happiness Report. For more information about living in Finland: Why Finland? | Aalto University More info: twitter.com/fcai_fi linkedin.com/company/fcai youtube.com/channel/UC7nUhposDgxzDOKns_H5J0w Newsletter: http://eepurl.com/gVPBpf Aalto.fi twitter.com/aaltouniversity facebook.com/aaltouniversity instagram.com/aaltouniversity 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.
Salary
3100€ - 4200€
Posted
1 Jun 2026
Research Fellow / Engineer (Cement and Concrete) - ZMS2
Singapore Institute of Technology (SIT)
Singapore
Singapore Institute of Technology (SIT)
Singapore
Schemes of Service: Research Division: Engineering Employment Type: Fixed Term 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. Key Responsibilities Lead and support the execution of the research project in collaboration with the Principal Investigator (PI), Co-PI, and research team, ensuring timely delivery of project milestones, technical outputs, and reporting requirements. Design and conduct experimental programmes for ultra-low carbon concrete systems, including LC3- and steel slag-based materials, as well as steel fibre reinforced concrete (SFRC), covering materials development, mix design optimisation, and performance evaluation. Perform advanced materials characterisation and microstructural analysis, including but not limited to: i. X-ray Fluorescence (XRF) ii. X-ray Diffraction (XRD) iii. Scanning Electron Microscopy with Energy Dispersive X-ray Spectroscopy (SEM-EDX) iv. Thermogravimetric Analysis (TGA) v. Isothermal calorimetry vi. Fourier Transform Infrared Spectroscopy (FTIR) Analyse hydration mechanisms, strength development, fibre–matrix interaction, and phase evolution, and correlate microstructural characteristics with macroscopic performance. Conduct comprehensive mechanical testing of concrete, including strength, stiffness, toughness, crack control behaviour, and post-cracking performance (particularly for SFRC), as well as structural performance assessments. Evaluate durability performance and long-term behaviour, including resistance to chloride ingress, carbonation, permeability, fibre corrosion (where applicable), and other degradation mechanisms relevant to structural applications. Support pilot-scale production, test-bedding, and field implementation to validate material performance under real-world conditions. Prepare technical reports, publications, and presentations to disseminate research findings to academic, industry, and regulatory stakeholders. Carry out risk assessments and ensure full compliance with Workplace Safety and Health (WSH) regulations and laboratory safety protocols. Manage procurement processes, including specification development, vendor coordination, and equipment acquisition. Ensure proper operation, calibration, and maintenance of laboratory equipment, working both independently and collaboratively within the research team.luding scaling up mix designs, addressing variability in industrial materials, and aligning with relevant standards and specifications. Managing uncertainties associated with emerging low-carbon materials, including variability in by-product sources (e.g., steel slag), performance consistency, and acceptance by industry stakeholders. Job Requirements Master’s degree in Materials Science (specialising in cement and concrete), Civil Engineering, or a related discipline; a PhD will be an advantage. Demonstrated knowledge and hands-on experience in cementitious materials and concrete characterisation, particularly in limestone calcined clay cement (LC³), carbonated steel slag-based systems, and steel fibre reinforced concrete (SFRC). Strong understanding of cement chemistry, hydration mechanisms, fibre–matrix interaction, and microstructural development of advanced cementitious composites. Practical experience with materials characterisation techniques such as XRF, XRD, SEM-EDX, TGA, calorimetry, and FTIR will be advantageous. Experience in mechanical and durability testing of concrete, including strength, toughness, crack control behaviour (especially for SFRC), permeability, and long-term performance assessment. Familiarity with laboratory practices, equipment operation, and safety protocols in materials testing environments. Ability to work both independently and collaboratively in a multidisciplinary research team. Strong analytical, problem-solving, and technical writing skills, with the ability to translate research findings into practical engineering and industry applications. Key Competencies The candidate should demonstrate the following competencies: Ability to build and maintain effective working relationships with internal and external stakeholders, including academia, industry partners, and vendors. Self-directed learner with a strong commitment to continuous learning and professional development in emerging materials and construction technologies. Strong technical writing and presentation skills, with the ability to communicate complex research outcomes clearly to both technical and non-technical audiences. Excellent analytical and critical thinking skills, with the ability to interpret experimental data and derive meaningful engineering insights. High level of initiative, accountability, and ownership in delivering high-quality work and meeting project timelines. Ability to work effectively both independently and collaboratively within multidisciplinary research teams.
Salary
Competitive
Posted
1 Jun 2026
