Pacific University

Part-time (0.4 FTE) 12-month fixed-term opportunity Be part of The Poche Centre for Indigenous Health and contribute to impactful, community-driven research that creates meaningful change Base Salary $127,436 (pro-rata) + 17% superannuation About the opportunity This position is targeted for Aboriginal and Torres Strait Islander people, under the provisions of section 126 of the Anti-Discrimination Act 1977 (NSW).' Should your application be progressed, you will be required to provide your confirmation of identity documents, if applicable. Your recruiter will be in touch to advise you on how to confirm Aboriginal and Torres Strait Islander status. Click here to read the Faculty of Medicine and Health, First Nations Employment Brochure. Join The Poche Centre for Indigenous Health, part of the University of Sydney, a leading centre dedicated to advancing research, policy, and practice in Indigenous health. The Poche Centre brings together a dynamic team of researchers, clinicians, and collaborators working to generate impactful knowledge, inform policy, and improve health outcomes across communities. We are seeking a talented Research Fellow to join our team. This role offers the opportunity to work both independently and as part of a multidisciplinary team, translating research into meaningful outcomes across policy, practice, and community. You will play a key role in advancing research initiatives, supporting funding opportunities, and engaging with a broad network of stakeholders. As a subject matter expert, you will operate with a high degree of autonomy - providing advice, solving complex problems, and contributing to strategic research priorities within the Centre and broader University. Successful applicants will have opportunities to engage in research projects that include a focus on social and emotional wellbeing, mental health, breastfeeding and food security. Your key responsibilities will be to: Conduct high-quality research independently and collaboratively, contributing to publications, conference presentations, and funding outcomes. Develop and maintain a strong research profile through peer-reviewed publications, scholarly outputs, and active participation in academic forums. Build and sustain research collaborations, including translational research that drives impact across policy, practice, industry, and community. Contribute to the preparation of competitive research grant and funding applications. Supervise and mentor postgraduate research students and provide guidance to early-career academics where appropriate. Contribute to administrative activities, stakeholder engagement, and a positive, inclusive workplace culture aligned with the University's strategic priorities. About you Completed PhD in Aboriginal and Torres Strait Islander Health, Mental Health, Social and Emotional Wellbeing. Demonstrated experience conducting original research and contributing to scholarly outputs, with a developing research profile in a relevant discipline. Proven ability to build and maintain relationships with academic, industry, and professional stakeholders, with an emerging collaborative network. Strong communication and presentation skills, with the ability to effectively convey complex ideas to diverse audiences. Well-developed planning and organisational skills, with the ability to manage competing priorities and deliver high-quality outcomes. Experience supervising or mentoring students or staff, supported by strong digital literacy and a service-oriented approach. 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 Your employment is conditional upon the completion of all role required pre-employment or background checks in terms satisfactory to the University. 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. This position is designated as involving child-related work. To undertake or remain in this position, you are required to apply for and obtain a Working with Children Check clearance in accordance with the Child Protection (Working with Children) Act 2012. 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 Roshik Prasad, Recruitment Operations by email to roshik.prasad@sydney.edu.au Copyright 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 Saturday 02 May 2026 11:59 PM

As one of Europe’s leading research universities, Ludwig-Maximilians-Universität (LMU) in Munich is committed to the highest international standards of excellence in research and teaching. Building on its more than 500-year-long tradition, it offers a broad spectrum that covers all areas of knowledge within its 18 Faculties, ranging from the humanities, law, economics and social sciences, to medicine and the natural sciences. The Faculty of Languages and Literatures invites applications for a Professorship (W2) (6 years/tenure track)  of Comparative Literature and Literary Theory commencing as soon as possible. The applicant’s work in the field of Comparative Literature must be indicative of philological expertise in at least two different languages. Research interests in literary theory and/or aesthetics as well as literary multilingualism are required. A focus on English-language literature is also desirable. LMU Munich seeks to appoint a highly qualified junior academic to this professorship and, therefore, especially encourages early-career scholars to apply. Prerequisites for this position are a university degree and a doctoral degree or a comparable specific qualification, preferably in Comparative Literature. With an excellent record in research and teaching to date, prospective candidates will have demonstrated the potential for an outstanding academic career. The initial appointment will be for six years. After a minimum of three years, it can be converted into a permanent position pending a positive evaluation of the candidate’s performance in research and teaching as well as his or her personal aptitude and if all legal conditions are met. Under the terms of the LMU Academic Career Program“, in exceptional cases and subject to outstanding performance in research and teaching, the position may be converted from a W2 into a W3 Full Professorship at a later date. LMU Munich makes a point of providing newly appointed professors with various types of support, such as welcoming services and assistance for dual career couples. LMU Munich is an equal opportunity employer. The University continues to be very successful in increasing the number of female faculty members and strongly encourages applications from female candidates. LMU Munich intends to enhance the diversity of its faculty members. Furthermore, disabled candidates with essentially equal qualifications will be given preference. Please submit your application comprising a curriculum vitae, documentation of academic degrees and certificates as well as a list of publications and teaching to the Dean of the Faculty of Languages and Literatures, Ludwig-Maximilians-Universität München (Geschwister-Scholl-Platz 1, D-80539 Munich, Germany), preferably via email in one single PDF-file to dekanat13@lmu.de, no later than 28 April 2026.

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. This project focuses on federated causal inference in heterogeneous data environments, addressing the challenge of enabling trustworthy causal analysis across distributed datasets while preserving privacy. The successful candidate will be responsible for the end-to-end investigation of novel federated learning strategies for causal inference. The role will bridge rigorous theoretical work with hands-on algorithm design and development on real-world datasets. The core responsibility is to build and validate federated causal inference algorithms through simulations and live demonstrations. Key Responsibilities Participate in and manage the research project with Principal Investigator (PI) to ensure all project deliverables are met. Derivation of novel performance metrics for federated causal inference algorithms. Analysis of causal inference models in federated settings using synthetic and real-world datasets. Design and development of novel federated causal inference algorithms and associated software APIs. Validation of algorithms via simulations and live demonstrations. Job Requirements A Master's degree or higher in Computer Engineering, Computer Science, Data Science, Statistics, or equivalent. Strong theoretical background in statistics and machine learning. Knowledge of the basics of federated learning and causal inference is highly encouraged. Proven track record in research and development of machine learning algorithms. Proficiency in algorithm development using Python and ML frameworks such as PyTorch or TensorFlow. Key Competencies Work independently, as well as within a team, to ensure proper operation and maintenance of equipment. Able to build and maintain strong working relationships with people within and external to the university. Self-directed learner who believes in continuous learning and development. Proficient in technical writing and presentation. Possess strong analytical and critical thinking skills.