University of La Laguna

Advert reference: uj_002321 Advert status: Online Apply by: 3 May 2026 Position Summary Industry: Education & Training Job category: Education and Training Campus: Auckland Park Kingsway Campus Contract: Permanent Remuneration: Market related EE position: Open to all Level: Skilled Introduction The University of Johannesburg (UJ) is a vibrant and cosmopolitan institution, guided by its bold UJ Strategy 2035, which emphasises Societal Impact and Sustainability, Global Footprint and Partnerships, and Technology for the Future. Committed to transformative change, UJ’s mission is “To transform and serve humanity through innovation and the collective and collaborative pursuit of knowledge.” The University is guided by the vision of building “An international university of choice, anchored in Africa and the global south, dynamically shaping a sustainable future" Job description “Please note that the University is obligated, in terms of recent amendments to the Criminal Law (Sexual Offences and Related Matters) Amendment Act 2021 (Act 13 of 2021), to assess all prospective employees (including applicants) against the National Register for Sex Offenders (NRSO). The outcome of such an assessment may have an impact upon possible employment with the University. For more information, please review the following link: Justice/Criminal/NRSO The Johannesburg Business School (JBS) is a young and dynamic business school of UJ. The JBS supports the vision and objectives of UJ and therefore focus on sustainability and societal impact as well as technologies of the future, specifically through a focus on Digital Transformation in all the curricula and offerings. JBS delivers its PGDip and MBA as both face-to face and online. A DPhil programme is also offered with a focus on Digital Transformation. Academics in JBS have the opportunity to grow and develop in their academic career through teaching and research. Job Purpose: The role is responsible to lead the teaching and research on Digital Transformation towards the fulfilment of the mission of JBS. Responsibilities: Teaching and Learning Develop and deliver high-quality, well-structured modules that enhance student success. Lead and contribute to the development of new and revised learning materials for updated and newly introduced modules. Integrate Fourth Industrial Revolution (4IR) principles into the design and development of course content. Ensure full compliance with all tuition policies, academic procedures, and institutional standards. Draft, review, and oversee the setting of assignments, tests, and examination papers. Take responsibility for the external moderation of assessments to ensure academic quality and integrity. Mark and moderate assessments within prescribed turnaround times. Design and implement effective strategies to improve student retention and reduce dropout rates. Supervise postgraduate students successfully through the duration of their studies. Research and Innovation Produce quality research outputs, including accredited journal articles, book chapters, books, and conference proceedings. Publish thought leadership and opinion pieces on 4IR topics in the popular press. Prepare and submit grant applications to secure funding for research and development initiatives. Collaborate with international academic and industry partners to enrich curriculum development, teaching excellence, and strategic partnerships that enhance the stature of JBS. Strategic and Operational Academic Leadership Drive and implement innovative teaching, learning, and research practices. Actively participate in JBS committees and institutional academic forums. Provide mentorship and academic leadership to colleagues within the discipline or subject area. Minimum requirements A doctoral degree (NQF 10) in Artificial Intelligence, or relevant field. AI technologies and its applications, including related programming languages and software tools. International cooperation as well as engaging with industry, and to secure funding for research and development on impact of digital transformation on business, people and society. Proven record of excellence in accredited research outputs, supervision and in the teaching and assessment at university level. Small and Medium Sized Enterprises (SME) experience (working in, or consulting with SMEs). Deep understanding of South African and African business education. Multi-disciplinary knowledge. Recommendations: An excellent teaching portfolio at a reputable Higher Education Institution, able to teach large groups of 50 to 150 students, preferably in the business school context. Excellence in postgraduate research supervision and publications. Ability to develop programme outcomes and module content at DPhil, MBA, PDBA and Executive Development Levels. Industry-related experience. Competencies and Behavioural Attributes: Exceptional written and oral communication skills and the ability to adapt communication to a range of audiences. Self-management (good planning, time management, prioritising and organising skills). Teamwork. Result driven. Good interpersonal skills. Good listening skills. Good financial management and budgeting skills. Problem solving and systems level thinking. Enquiries: Enquiries regarding the job content: Prof Adri Drotskie at Tel: (011) 559 1840 Enquiries regarding remuneration & benefits: Mrs Chandni Hira-Fakir (HCM Business Partner) at Tel: (011) 559 3885

At the University of Vienna, almost 11,000 people work together on the big questions of the future. Approximately 7,700 of them are academic staff members. These are individuals who, with their curiosity and their continuous pursuit of excellence, engage in international cutting-edge research and teaching. With us, you will also find space to unfold your potential. We are offering PhD Positions in Responsible AI 39 Faculty of Computer Science Startdate: 01.08.2026 | Working hours: 30 | Collective bargaining agreement: §48 VwGr. B1 Grundstufe (praedoc) Limited until: 01.08.2029 Reference no.: 5509 The employment duration is 3 years. Initially limited to 1.5 years, the employment relationship is automatically extended to 3 years if the employer does not terminate it within the first 12 months by submitting a declaration of non-extension. With appropriate work progress, an extension to a total maximum of 4 years is possible. About the team Join the Responsible Machine Learning (ML) Group at the Faculty of Computer Science. Led by Prof. Dr. Martin Pawelczyk, who recently joined the University of Vienna from Harvard University, our research sits at the intersection of AI Safety and Data-Centric AI. We aim to make large-scale ML more reliable, transparent, and aligned with human values. We are specifically interested in: Data-centric AI: Advancing machine unlearning, privacy-preserving techniques, and robust data curation. AI Safety: Ensuring robust alignment and safety in multi-agent LLM systems Efficiency:  Streamlining large-scale model experimentation and training. Science of Deep Learning: Exploring mechanistic interpretability and understanding the fundamental drivers of model performance at scale. As an early member of this fast-growing team, you will have a unique opportunity to shape our research culture and contribute to high-impact projects from the ground up. We are currently hiring a founding cohort of 3 PhD researchers to tackle high-impact projects across our core focus areas.  We are looking for curious minds who are excited to push the boundaries of responsible AI. Learn more about the lab's work at: https://martinpawelczyk.github.io/. Tasks and Responsibilities Develop machine learning methods and tools with a specific focus on: Data-Centric AI: Including data attribution, data curation, and privacy preservation for large foundation models (e.g., LLMs and VLMs); Agentic AI: Exploring multi-agent systems and their dynamics; Explainable AI: With a particular emphasis on mechanistic interpretability. Invent, evaluate, and publish novel algorithms, aiming for theoretical guarantees when working with structured and unstructured data. Pursue and complete a PhD thesis within the appointed 4-year duration. Join the Vienna Doctoral School of Computer Science and conclude a doctoral thesis agreement within 12 months. Present your research results at top-tier international conferences, workshops, and journals. Contribute to the academic community by assisting in the organization of international meetings, conferences, and symposia. Take on administrative responsibilities to support the research group and the Faculty of Computer Science. You hold courses and examinations independently and (co-)supervise students within the scope of the provisions of the collective bargaining agreement.  Your qualifications Must-haves A Master’s degree (completed or near completion) in Computer Science, Machine Learning, Mathematics, Physics, Statistics, or a related quantitative field.  A solid background in machine learning, statistics and/or mathematics. Strong programming skills in Python. Ideally, also proficiency in at least one major deep learning framework (e.g., PyTorch, JAX). An early track record of research (e.g., a high-quality Master's thesis, open-source contributions, or workshop papers).  Excellent command of written and spoken English, as we operate in a global research environment. A high degree of intrinsic motivation, curiosity, and the ability to work both independently and collaboratively. Desirable skills Experience in training or fine-tuning large-scale models (LLMs, VLMs) in distributed settings. Familiarity with cluster computing environments (e.g., SLURM) and Linux-based workflows. Prior experience in a research lab, including contributions to publications or significant open-source projects. Teaching experience. What we offer Competetive Compensation: A full-time salary of EUR 3,776.10 (on a full-time basis, paid 14 times a year) which may increase if we can credit professional experience. World-Class Location: Live and work in Vienna, consistently ranked as the world's most livable city, with our office easily accessible via excellent public transport. Inspiring work atmosphere: Become part of an international academic team in a healthy and collaborative working environment. Training and Coaching: Opportunity to deepen your skills on an ongoing basis. There are over 600 courses to choose from – free of charge. Contract Structure: The planned employment duration is up to 4 years. Following standard university procedures, the initial contract is for 1.5 years. This automatically extends to 3 years – and subsequently up to 4 years based on research progress – following a successful mutual evaluation in the first 12 months. What you need to apply Academic curriculum vitae Cover letter (State the earliest start date and your motivation to apply.) A copy of your thesis (or an extended abstract if still in progress) Official transcripts for both your Bachelor's and Master's degrees Fill out this form (optional but encouraged): https://tinyurl.com/mvamwy7a  If you have any questions, please contact: Martin Pawelczyk martin.pawelczyk@univie.ac.at We look forward to welcoming new talent in our team! The University of Vienna has an anti-discriminatory employment policy and attaches great importance to equal opportunities, the advancement of women and diversity. We place particular emphasis on enhancing women’s representation among the academic and general university staff, particularly in leadership roles, and therefore expressly encourage qualified women to apply. Given equal qualifications, preference will be given to female candidates. University of Vienna. Space for personalities. Since 1365. Data protection ​Application deadline: 05/20/2026 Prae Doc

Full Time, Fixed Term and Ongoing positions Salary level HEW 8 + 17% Superannuation and Flexible Working Arrangements Based on the Melbourne CBD campus, however, may be required to work and/or be based at other campuses of the University. Great benefits such as 17% Super, generous annual, personal and parental leave, Employee Assistance Program, Medical Hub on Campus, Novated Car Leasing, 25% discount on some short courses, personal software discounts, among others About You As a Quality Lead, you are a collaborative and experienced quality professional with a strong background in vocational education and training. You have proven expertise in developing and assuring compliant training and assessment strategies, and in supporting educators to deliver high-quality learning experiences. You are confident leading and coaching teams, building staff capability in compliance requirements, and driving continuous improvement initiatives such as validation and quality assurance processes. You work effectively across teams to co-design innovative and consistent learning and assessment solutions. With strong communication and stakeholder engagement skills, you contribute to enhancing both compliance outcomes and the overall student experience, while supporting a culture of quality, collaboration and excellence. To be successful in this position, you'll have: Expert knowledge of assessment requirements of Training Package qualifications and accredited courses i.e. vocational education competency-based training, ASQA, AQF and CRICOS requirements. Experience in the development of training & assessment tools and processes applicable to a range of business programs or disciplines in a vocational educational setting. Highly developed skills in vocational assessment design and mapping assessment tools to the training package units of competency I.e. elements, performance criteria, skills, knowledge and assessment conditions and/or range statement and principles of assessment (Reliability, Fairness, Flexibility and Validity) and rules of evidence (Validity, Currency, Sufficiency and Authenticity). Experience in project management in education environments, capacity to lead through influence and proven ability to meet deadlines and project milestones. Excellent interpersonal skills, demonstrating the ability to work collaboratively with staff across all levels from a coaching and development perspective. Qualifications An Australian Qualifications Framework (AQF) Level 5 Diploma or above in teaching and learning which includes supervised teaching practice and studies in teaching methodology or equivalent qualification accepted by the University. Please Note: Appointment to this position is subject to passing a Working with Children and National Police Check. To Apply Please submit your CV and covering letter addressing your interest and suitability for this position by clicking on the 'Apply' link at the top of this page. For further information about this position, please see Position Description below or contact Diana (Talent Acquisition) via email diana.ruiz@rmit.edu.au. Position Description - Quality Lead Why work at RMIT University Our people make everything at the University possible. We encourage new approaches to work and learning, stimulating change to drive positive impact. Find out more about working at RMIT University, what we stand for and why we are an Employer of Choice. We want to attract those who will make a difference. View RMIT's impressive standings in university rankings. https://www.rmit.edu.au/about/facts-figures/reputation-and-rankings #LI-Hybrid