Mukah Polytechnic

Based in College of Health at the Women’s and Children's Hospital Multiple Part-time (0.5FTE), 12-month fixed term contracts Unique opportunity for a joint role across Adelaide University and the Women’s and Children’s Hospital Exciting Senior Lecturer role in the School of Medicine, Discipline of Paediatrics and joint appointment with the Women’s & Children’s Health Network (WCHN). At Adelaide University, we create the opportunities you need to achieve your ambitions – because when you thrive, we thrive. We are transforming education for contemporary learners and global citizens. Building on a proud legacy and shaped by bold ambition, it’s a place of excellence and equity, where our vibrant community of staff are united by our purpose to inspire Australia’s future change-makers and create a better tomorrow. Work that matters The School of Medicine provides an innovative and collaborative research and teaching environment.  We are seeking to appoint multiple part–time Senior Lecturers in the Department of Paediatrics as a joint appointment with WCHN, and who will participate in the delivery of clinical services in Paediatrics in one of the following specialities: Infectious Diseases, Respiratory. The appointee will be based at the Women’s & Children’s Hospital and will be expected to participate in the delivery of clinical services and supervise junior medical staff. The appointee will provide leadership in teaching and research for the School of Medicine, as determined by the needs of the School. The team The appointee will report to the Academic Lead WCH Precinct, as the nominee of the Dean of Medicine, School of Medicine, College of Health for teaching and research related activities, and to the Head of Clinical Unit, WCHN for clinical duties. Visit the AU website to learn more about College of Health. Our people Our people are guided by purpose, curiosity and a commitment to lifelong learning. We embrace authenticity, innovation and collaboration, and harness diverse thinking in our pursuit of excellence. This role is perfect for someone who enjoys variety and meeting new people. You will experience a range of tasks and interactions as the organisation establishes its new identity, keeping your workday interesting and engaging. You will be part of a resilient team that values flexibility and proactive problem-solving, empowering you to drive success in a constantly evolving workplace. You will work alongside a diverse community of colleagues, access state-of-the-art facilities, and contribute to a broad range of teaching and research activities—ensuring your work remains engaging, meaningful, and impactful. Learn more about our people, what we stand for and what we offer at Careers at AU. Experience To join our community and thrive in this role, you will likely have the following skills and experience: Adelaide University: Demonstrated excellence in teaching undergraduate and post-graduate students in a clinical and academic setting    Demonstrated experience in conducting and publishing high quality research in a recognised area of Paediatrics             Engaging in medical teaching programs Women’s and Children’s Health Network: Clinical Delivery Clinical Leadership  Clinical Administration  Essential Registered as a medical practitioner and specialist paediatrician with AHPRA FRACP (or equivalent) Track record in research and teaching commensurate with level Higher research degree (e.g; MD or PhD), or equivalent body of work Desired Experience in provision of paediatric care in a tertiary referral centre Our commitment to inclusion and diversity We are committed to fostering a culture of inclusion where diversity is celebrated and everyone feels respected and valued. Adelaide University is an equal opportunity employer, committed to creating a safe, inclusive, and equitable workplace where everyone can thrive. We strongly encourage applications from Aboriginal and Torres Strait Islander peoples, people with disability, and people of all ages, genders, cultural backgrounds, sexual orientations, and gender identities. We are committed to supporting flexible working arrangements and providing reasonable adjustments throughout the recruitment process. Launch your future with Adelaide University now Applying is simple. Simply click on the Apply Now button and upload:  your current CV  a cover letter that tells us why you’re excited about the role The online application form will list the specific selection criteria that you need to address. Submit your application by 11:30pm Closing Date Thursday 19th March 2026 The University reserves the right to close this advertisement before the closing date if a suitable candidate is identified. For further information about this opportunity, please contact (quoting reference number 492726): Professor Jenny Couper, Academic Lead WCH Precinct, Discipline of Paediatrics and Department of Diabetes and Endocrinology, WCHN E: Jennifer.couper@adelaide.edu.au T: 8161 6242 Role not considering sponsorship Applications welcomed from Australian or NZ citizens, Australian permanent residents and those who have the legal right to work in Australia for the term of appointment.   WWCC clearance – if applicable Pursuant to the Child Safety (Prohibited Persons) Act 2016 (the Act) and the Child Safety (Prohibited Persons) Regulations 2019 (the Regulations), this position has been deemed prescribed. This role will require the successful candidate to hold a current Working with Children Check.  

The University of Vienna is a community of almost 11,000 individuals, including approximately 7,700 academic staff members, who passionately pursue answers to the profound questions that shape our future. They represent individuals driven by curiosity and a relentless pursuit of excellence. With us, they find the space to try things out and unfold their potential. Are you inspired by their passion and determination? We are currently seeking a/an University assistant predoctoral - PhD Position in Graph Learning 39 Faculty of Computer Science Startdate: 01.05.2026 | Working hours: 30 | Collective bargaining agreement: §48 VwGr. B1 Grundstufe (praedoc) Limited until: 30.04.2029 Reference no.: 5311 Your responsibilities: As a University assistant, you will contribute to the work group Machine Learning with Graphs led by Prof. Nils M. Kriege. Our research focuses on the development of new methods and learning algorithms for structured data. Graphs and networks are ubiquitous in various domains from chem- and bioinformatics to computer vision and social network analysis. Machine learning with graphs aims at exploiting the potential of the growing amount of structured data in all these areas to automate, accelerate and improve decision making. Analysing graph data requires solving problems at the boundaries of machine learning, graph theory, and algorithmics. Your future tasks: You actively participate in research, teaching & administration, which means: You are involved in research projects in the area of graph learning. You are working on scientific articles to publish your research results. You attend scientific conferences to present your research. We expect you to finalize your dissertation agreement within 12 months. You work on your dissertation and its completion. You contribute to courses independently within the scope of the provisions of the collective bargaining agreement. You take on administrative tasks in research, teaching and administration. Your research should be situated in the field of machine learning with graphs and may address both theoretical and practical questions. The aim is to analyse and develop new, well-founded methods and learning algorithms that extend the boundaries of existing techniques - for example, with respect to expressivity, generalization, interpretability, or scalability. This is part of your personality: Completed Master's degree or Diploma, in the field of computer science or a related field (Applications from candidates who are close to completing their studies are welcome; hiring can only take place once the Master’s/Diploma degree has been completed.) Solid background or strong interest in machine learning, graph theory, and their mathematical foundations. Solid programming skills Experience with machine learning libraries or willingness to acquire Excellent command of English Ability to work in a team Desireable qualifications: Basic experience in research methods and academic writing Teaching experience What we offer: 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 base salary is EUR 3.776,10 (full-time employement basis; 14 payments per year); it increases if we can credit professional experience. Tenure: 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. Application documents: Academic curriculum vitae  Letter of Motivation including ideas for a prospective doctoral project Abstract of master´s thesis Master´s Degree / Diploma certificates Transcript of records List of publications, evidence of teaching experience (if available) If you have any questions, please contact: Nils Morten Kriege nils.kriege@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: 03/26/2026 Prae Doc

Ref.: 534545 Work type: Full-time Department: Department of Mathematics (25500) Categories: Teaching Staff Teaching Assistant in the Department of Mathematics (Ref.: 534545) (to commence on September 1, 2026 or as soon as possible thereafter for one year, with the possibility of renewal subject to satisfactory performance) Applicants should possess a Master’s degree or above in Pure or Applied Mathematics or related fields, such as Statistics and Computer Science. The appointee will assist in delivering courses and tutorials at undergraduate and/or postgraduate level(s), and provide general teaching and administrative support to the Department. A highly competitive salary commensurate with qualifications and experience will be offered, in addition to annual leave and medical benefits. The University only accepts online application for the above post. Applicants should apply online and upload a covering letter together with an up-to-date C.V. Review of applications will commence as soon as possible and continue until March 31, 2026, or until the post is filled, whichever is earlier. The University is an equal opportunities employer and is committed to equality, ethics, inclusivity, diversity and transparency