Shahid Rajaee Teacher Training University

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

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 looking for a/an ... Scientific project assistant predoctoral 37 Faculty of Business, Economics and Statistics Startdate: 01.06.2026 | Working hours: 30 | Collective bargaining agreement: §48 VwGr. B1 Grundstufe (praedoc) Reference no.: 5569 Explore and teach at the University of Vienna, where more than 7,500 academics thrive on curiosity in continuous exploration and help us better understand our world. Does this sound like you? Then join our accomplished team! Your personal sphere of influence: The research group Statistical Analysis and Inference (STAIN) (https://stain.univie.ac.at/) at the Department of Statistics and Operations Research (https://isor.univie.ac.at/), University of Vienna, is offering a PhD position in the area of Mathematical Statistics and Machine Learning, starting at the earliest possible date, and no later than September. The doctoral position is funded within the framework of a FWF project and is part of the DFG–FWF Research Unit 5381 (https://for5381.uni-freiburg.de/en/research-unit-5381/). The Research Unit offers a highly stimulating and collaborative research environment, including numerous scientific events, workshops, and joint activities, from which early‑career researchers benefit particularly strongly. Your future tasks: You actively participate in research and administration, which means: In collaboration with your advisor you will develop and complete your own PhD-project in the area of mathematical statistics or the theory of machine learning. We expect you to finalize your dissertation agreement (= project proposal) within 12-18 months and that you regularly participate in the PhD seminar. You get acquainted with a recent research area, formulate new and relevant mathematical problems and solve them independently under the supervision of your PhD advisor. You take on administrative tasks in research. You work on your own publications, academic articles and presentations. This is part of your personality: Completed Master's degree or diploma, in the field of statistics, mathematics or a closely related field (completed or about to be completed). A strong background in mathematical statistics and probability theory. Enthusiasm for abstract mathematical problems and strong tenacity and patience in solving them. Active interaction and discussion with the colleagues from the research group and the department. Programming skills. Didactic competences / experience with e-learning. Excellent command of written and spoken English (C1 Level). What we offer: 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. Work-life balance: Our employees enjoy flexible working hours and can partially work remotely. Inspiring working atmosphere: You are a part of an international academic team in a healthy and fair working environment. Good public transport connections: Your workplace is easily accessible by public transport. Internal further training & Coaching: Opportunity to deepen your skills on an ongoing basis. There are over 600 courses to choose from – free of charge. Fair salary: The basic salary of EUR 3.776,10 (on a full-time basis) increases if we can credit professional experience. Equal opportunities for all: We welcome every additional/new personality to the team! It is that easy to apply: With your scientific curriculum vitae. With a letter of intent outlining especially your previous experience with mathematical problem solving (max. 1 page). With your summary of research interests (max. 1 page) With contact details of at least two persons who agreed to provide reference letters upon request. Transcripts and Master Degree  /  Diploma (if available). Via our job portal/ Apply now -  button. If you have any questions, please contact: Johannes Moritz Jirak moritz.jirak@univie.ac.at We look forward to new personalities 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: 05/11/2026

Classification: Academic Level A/B Salary package: $89,313 - $137,870 per annum plus 17% superannuation Term: Full-time, Fixed Term (Up to December 2027) The Position Up to two academic positions are available for the project “Analytics for the Australian Grains Industry” (AAGI) within the Research School of Finance, Actuarial Studies and Statistics at the ANU College of Business and Economics. The successful candidate will undertake a collaboratively designed research program in statistical design and modelling, while also providing analytical support to projects relevant to the Australian grains industry. This position will be part of a partnership between ANU and the Strategic Partners (Curtin University, University of Queensland, and University of Adelaide) of the Analytics for the Australian Grains Industry (AAGI). The Person We are looking for academics with a PhD (or who will be awarded a PhD within six months of the appointment commencement) and experience in statistics, data science, machine learning, bioinformatics, quantitative biology, or closely related fields. Candidates must possess strong scientific programming skills, demonstrated experience working with real data, and a substantial commitment to reproducible and transparent workflows. They should also have evidence of experience relevant to the fields of data science, data analytics, statistics, machine learning, bioinformatics, or quantitative biology. To be considered to be appointed at Academic Level B, candidates should provide evidence of their ability to articulate and pursue innovative research in the fields of data science, data analytics, statistics, machine learning, bioinformatics, or quantitative biology. They should also present a vision for the activities they will undertake at ANU. The candidate should have working rights and be available to start by August 2026. Desirable Requirements: Experience in mixed models, experimental design, image analytics, machine learning, transcriptomics, or molecular phenotyping. Experience in the biological or agricultural sciences. For more information about the position please contact Dr Emi Tanaka on E: Emi.Tanaka@anu.edu.au Working at ANU This is an opportunity to work with a world class University that undertakes cutting edge research and has a strong tradition in research-led teaching excellence. For information on a range of lifestyle, financial and non-financial rewards and programs, please click here. The ANU College of Business and Economics (CBE) seeks to advance knowledge through high quality teaching and research. We contribute to associated professions, industry and government by conducting world-class, long-term strategic research, and through the provision of a range of specialised undergraduate and postgraduate degree programs. As a part of Australia's leading university, CBE provides an excellent educational experience for our students. Our global alumni network reaches the world's leading companies, policy agencies and universities. We strongly believe that the way in which we operate is defined by our Values and Behaviours and encourage you to apply if you are looking for a workplace that encourages respect, collegiality and excellence. To Apply To be considered for this position, please upload the following documents: A current curriculum vitae (CV), and No more than a two-page summary addressing your suitability against the selection criteria. The committee will consider candidates that do not meet one or more aspects of the selection criteria. Please note: The successful candidate must have rights to live and work in this country and will be required to undergo a background check during the recruitment process. An offer of employment is conditional on satisfactory results.