University of Passo Fundo (UPF)

Full time continuing role Exciting opportunity to join the Commercialisation Office team at the University of Sydney and help commercialise technologies in the Medtech and Biotech sectors Base Salary HEO9 $146,197 - $154,260 + 17% superannuation About the opportunity Reporting to the Head of Commercialisation, you will work with the Faculty of Medicine and Health, one of the largest in the country, along with other Faculties and Research Partners to identify Intellectual Property (IP) suitable for commercial development and translation and develop and execute different commercialisation pathways. With a track record managing IP and commercialisation of research or similar commercial experience in the medtech or biotech sector you will develop and facilitate engagement between researchers, industry and investors to optimise the translation of the University's research, technology, and expertise. Your key responsibilities will be to: provide support and advice to researchers to develop, protect and effectively leverage their Intellectual Property into commercial products or services work collaboratively with internal stakeholders including researchers and other functions to identify IP and potential commercial partners evaluate the commercial potential and help protect IP generated from the University's research develop and negotiate commercial arrangements including agreements to license University IP or set up new ventures to commercialise the IP manage a Commercialisation Associate within the Commercialisation Office work with other parts of the University innovation ecosystem to develop and deliver entrepreneurial and commercialisation workshops and training programs for researchers. About you tertiary qualification in medicine, health or life sciences, biotechnology commercial experience the medtech, pharmaceuticals or biotech industry, or in a university tech transfer environment experience in developing commercial agreements and undertaking successful negotiations proven experience in IP identification, customer and market validation, business planning knowledge in intellectual property protection and management experience working in or developing new ventures to commercialise deep tech is highly desirable a thorough understanding of the innovation or commercialisation lifecycle and key issues at different stages able to assess industrial applicability of advanced technology, associated business development and marketing of academic research well-developed network in industry or venture capital community is highly desirable. Sponsorship / work rights for Australia You must have unrestricted work rights in Australia for the duration of this employment to be eligible to apply. Visa sponsorship is not available for this appointment. Pre-employment checks and declarations Your employment is conditional upon the successful completion of all pre-employment or background checks required for the role in terms satisfactory to the University. Also, to meet the University's obligations under the National Higher Education Code to Prevent and Eliminate Gender-Based Violence you will be asked to declare if you have been investigated for, or found to engaged in, sexual harm or gender-based violence in the course of previous employment or in a legal process. Similarly, your ongoing employment is conditional upon the satisfactory maintenance of all relevant clearances and background check requirements. If you do not meet these conditions, the University may take any necessary step, including the termination of your employment. EEO statement At the University of Sydney, our shared values are trust, accountability and excellence and we strive to be a place where everyone can thrive. We are committed to creating a University community that thrives through diversity and reflects the wider community that we serve. We deliver on this through our commitment to diversity and inclusion, evidenced by our people and culture programs, as well as key strategies to increase participation and support the careers of Aboriginal and Torres Strait Islander People, women, people living with a disability, people from culturally and linguistically diverse backgrounds, and those who identify as LGBTQIA+. We welcome applications from candidates from all backgrounds. We are proud to be recognised as an Australian Workplace Equality Index (AWEI) Platinum Employer. Find out more about our work on diversity and inclusion. How to apply Applications (including a cover letter, CV, and any additional supporting documentation) can be submitted via the Apply button at the top of the page. For employees of the University or contingent workers, please login into your Workday account and navigate to the Career icon on your Dashboard. Click on USYD Find Jobs and apply. For a confidential discussion about the role, or if you require reasonable adjustment or any documents in alternate formats, please contact Liam Newson, Recruitment Operations by email to liam.newson@sydney.edu.au © The University of Sydney The University reserves the right not to proceed with any appointment. Click to view the Position Description for this role Applications Close Sunday 14 June 2026 11:59 PM

The Vietnamese-German University (VGU) is seeking a highly qualified full-time lecturer in Building Construction and Component-Oriented CAD. Candidates must hold a Ph.D. in this field or a closely related field and have a strong background in research. Relevant international experience is of advantage. The successful candidate will become part of an international network of universities and research institutes. Teaching Responsibilities In the role of a lecturer, the successful candidate will teach undergraduate courses in the Civil Engineering and Construction Management (BCE) and related fields. The expected workload for the in-class lecture conduction is 08 academic hours per week, totaling 240 academic hours per year (1 academic hour equals to 45 minutes). Teaching should reflect current research methods and results, and comprises lectures on the following modules: Basics in Building Construction and Building Physics Building Construction Component-oriented CAD Computer-aided design Construction health and safety Project study 1 and Project Study 2 Technical drawing Engineering English Additional experiences in the fields of Building Physics are an asset. The named courses are subject to change upon realistic needs of the programs and joint agreement between the lecturer, relevant Academic Coordinators, and Dean/Vice Dean in charge of teaching. Courses may requires conducting relevant laboratory activities and/or advising student projects. The holder of this job is also responsible for supervising bachelor's and master's theses and mentoring Ph.D. students. Research Responsibilities As a faculty member of a research-oriented university, the successful candidate is expected to significantly contribute to the scientific profile of VGU through innovation. This includes and is not limited to comprehensive activities in basic research as well as applied research in the fields of construction management policy, environment assessment, and risk management. The ability to apply and generate externally funded research projects is highly desirable. A collaboration in research/services between the successful candidate and other programs and industry is envisaged. This also includes the management of the state-of-the-art geotechnical engineering laboratory at VGU. Administrative responsibilities The successful candidate is expected to contribute to the development of the Civil Engineering and Construction Management Program (BCE) by participating in administrative, marketing and other public activities of the program in consultation with the Academic Coordinator of the study program and the German partner university, namely Biberach University of Applied Sciences (HBC). She or he is also expected to contribute actively to the academic self-administration of the Faculty of Engineering and university by being willing to stand for election to the Faculty Council, Academic Senate and/or other bodies. Qualification Candidates must hold a Ph.D. in Civil Engineering or Construction Planning and/or a closely related field, preferably from a well-known international university. A current title of Professor will be a plus, as experience and understanding of the German higher education system and methodology. Other requirements include: An outstanding academic record with a focus on Building Construction or other areas closely related to it Proven expertise in Building Construction, Construction Component Design or Building Information Modelling Strong track record of successful research activities and publications in international and peer-reviewed journals in the related area Proven teaching experience with strong self-motivation in the mentioned teaching subjects combined with a passion for teaching and research Practical experience in the industry is an advantage Maintain strong connections with the construction industry through professional networks, industry collaborations, and guest lectures is a must Guide students in developing construction software skills (auto-CAD: construction and technical drawings; Sap2000, Etabs: Structural Analysis; Revit: Building 3D model etc.,) Guide students in developing industry connections through internships, site visits, and professional networking events Contribute to the professional development of civil engineering graduates by providing career guidance and mentorship Proven excellent English proficiency: Candidates who are from non-native English-speaking countries should include one of the following valid English proficiency certificates; IELTS 6.5, TOEFL 548(PBT), TOEFL 84 (iBT), TOEFL 212 (CBT), CEFR level B2 or Aptis level C1 at the time of application submission. Alternatively, candidates who do not hold a valid English proficiency certificate at the submission time need to be internally assessed at VGU to meet the criterion stated above.[1] Employment benefits The successful candidate will become part of a professional and interdisciplinary group of faculty and have access to state-of-the-art laboratories. VGU supports its lecturers with attractive start-up endowments for quality research projects. VGU also supports participation in national and international conferences and the publishing of research papers. VGU lecturers enjoy a rich cultural experience and a dynamic teaching environment through interactions with inquisitive and quality students. Further information, e.g. regarding the appointment procedure, the competitive salary and research activities can be downloaded here. Application To apply please send your application (with the following documents in one PDF max. size: 10 MB) to academicpositions@vgu.edu.vn with subject line "Building Construction and Component-Oriented CAD_[Your Name]" Your application should include: Form for basic information (Please download here, complete this form electronically and submit it together with your application) A cover letter stating your interest in joining VGU Curriculum Vitae (including list of publications) Scans of university degrees, university transcripts and other relevant certificates Scans of language certificates (if available, highly appreciated) References illustrating your professional and academic career, including contact details of references (if available, highly appreciated) Evaluation results for teaching (if available) All applications will be reviewed and evaluated by VGU's international Application Review Team. For further information, please contact: Program Academic Director: Prof. Dr.-Ing. Alexander Glock at glock@hochschule-bc.de and/or Program Academic Coordinator: Dr. Tien T. Nguyen at tien.nt@vgu.edu.vn About us The Vietnamese-German University (VGU) is a Vietnamese state university. Founded in 2008, VGU is a joint venture based on a close cooperation between the Federal Republic of Germany and the Socialist Republic of Vietnam, with the goal of becoming the leading research university in Vietnam and the region. VGU´s strategy is to customize excellent German study programs in the fields of engineering, informatics and economics to meet the needs of Vietnamese higher education. Being a joint effort of Vietnamese and German institutions, VGU follows the successful German model and standards concerning the academic and administrative structures. As part of VGU's ongoing commitment to gender equity, the university is actively seeking to enhance the representation of women in research and teaching roles. VGU therefore strongly encourages applications from qualified female lecturers who wish to contribute to the academic community.

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.