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Ratonga Matihiko | Digital Services Located in Ōtautahi | Christchurch, Aotearoa | New Zealand 5 weeks annual leave +5 days university holidays Professional development opportunities Generous superannuation provisions (up to 6.75% employer contribution) Full-time (37.5 hours per week), permanent position Kia hiwa rā, kia hiwa rā!He hiahia, he pūkenga nōu ki te mahi a te Data Scientist (AI Enablement)? Nāia te pōwhiri nā Te Whare Wānanga o Waitaha kia tono mai i te tūranga nei. Āu Mahi | What You Will DoAs a Data Scientist (AI Enablement), you will transform data into actionable insights and support decision-making across the University. You'll be part of the Data & AI Enablement team, working with faculties, professional services, and project teams to develop robust and interpretable modelling solutions that generate real-world value. Key Responsibilities Build, validate, and deploy statistical and machine learning models (e.g., regression, NLP, clustering). Evaluate and implement emerging AI patterns including Retrieval-Augmented Generation (RAG), AI agents, and orchestration frameworks to support university use cases. Design end-to-end solutions with strong focus on transparency, reproducibility, and performance. Explore and visualise datasets using Python and SQL to generate insights. Communicate results through reports and dashboards (e.g., Power BI). Trial generative AI applications and contribute to reusable AI templates and frameworks. Collaborate with stakeholders to define needs and deliver user-centred solutions. Uphold ethical data practices and UC’s commitments to Te Tiriti o Waitangi. Mōu | Who You AreTo be successful in this role, you will have: Bachelor’s degree in a relevant data science discipline (NZQA Level 7). At least 5 years of data engineering experience and 3+ years in data science/machine learning. Proficiency in Python, SQL, and cloud tools (Azure, DataBricks, Snowflake). Strong communication skills, business acumen, and stakeholder engagement experience. Commitment to cultural responsibility and UC values. Competency in te reo Māori me ōna tikanga is an advantage. An alignment with our organisation's values and culture, promoting a positive and inclusive work environment. Mahi Ngātahi | Who You Will Work WithBuilding world-class digital capability is crucial to the University of Canterbury's ongoing success. Digital Services is a large team, striving to provide a modern dynamic foundation from which the University (UC) can explore new business models and ways of working. Digital will transform how we work, behave, and the expectations of the communities we service Ngā Painga o UC | Why UCAt UC, being part of our team means more than just a job. We are committed to supporting our kaimahi | staff’s career and wellbeing with benefits designed to help our kaimahi grow and feel connected, supported and valued. UC’s Benefits approach is shaped by Ngā Uara | Our Values Whanaungatanga, Tiakitanga, and Manaakitanga. They are designed to be relevant, support and inspire our people, they include: 5 weeks annual leave +5 days university holidays UC Parental Leave (up to 9 weeks paid) + 26 weeks Government paid parental leave and onsite childcare facility generous employer contribution to superannuation (up to 6.75%) flexible working arrangements professional development and study opportunities supportive working environment a wide range of retail discounts across shopping, entertainment and travel on-campus staff discounts including UC RecCentre living in revitalised Ōtautahi | Christchurch, Aotearoa New Zealand a unique working environment in a beautiful campus with access to UC facilities such as UC RecCentre and Staff Club at discounted rates plus onsite cafés and eateries, and more. For more information, please visit us: https://www.canterbury.ac.nz/about-uc/work-at-uc/benefits-working-uc For more information about Te Whare Wānanga o Waitaha | University of Canterbury, please visit https://www.canterbury.ac.nz/ The closing date for this position is: 16 July 2026 (midnight, NZ time)Please note, applications will be reviewed as they are received, and interviews may take place before the close date. Pēhea te tono mai | How You Apply Applications for this position must be submitted via our careers website and should include a cover letter and resume. Please note, we do not accept applications by email, however we are happy to answer your queries in relation to the application process, please forward these to [email protected] You must have Aotearoa New Zealand or Australian citizenship/permanent residency or hold a valid NZ work visa to be considered for this role. Please note, this is an onsite position. Job Details Reference # 32534 Posted on 02 Jul 2026 Closes on 16 Jul 2026 23:55 Location(s) Christchurch Expertise Engineering, Information Technology, Science & Technology Job level(s) Experienced Work type(s) Continuing (Permanent) full-time More details (document) PD_Data Scientist.pdf Position description 1 Position description 2 Position description 3 Position description 4

Job DescriptionTe Whiwhinga mahi | The opportunity The Faculty of Medical and Health Sciences is seeking a Registered Nurse to support Year 3 medical students during the Clinical Methods Course – an important early introduction to clinical practice and the hospital environment.This role will be based at our Waitakere and North Shore campuses, respectively, and will involve identifying and consenting suitable inpatients to take part in bedside teaching alongside Clinical Methods Tutors (doctors) and students.Key responsibilities | Ngā kawenga matuaLiaise with ward staff to identify suitable inpatient volunteersApproach and assess patients for willingness and clinical appropriateness to participate in teaching sessionsObtain and document verbal consent in patient notesWhere appropriate, examine patients to confirm relevant clinical signsPrepare and share a patient list (including reserves) with Clinical Methods Tutors by 12.30pm each teaching dayEnsure patients are aware participation is voluntary and that they may not ultimately be selected by teaching staffAct with cultural sensitivity and prioritise patient wellbeing at all timesThis is a part time (11.25h), fixed term (8 weeks) opportunity.The salary range for this role is $73,400 - $90,700 (pro-rated) based on skills and experience.For more detailed information, please refer to the Position DescriptionHe kōrero mōu | About you You will be a New Zealand Registered Nurse with:A current Annual Practising CertificateA minimum of two years’ nursing experienceValid CPR and/or Advanced Life Support certificationYou will also demonstrate:Cultural competence and a respectful, inclusive approachStrong organisational and communication skillsThe ability to build effective relationships with clinical and academic colleaguesCalm, professional conduct in a fast-paced hospital environmentNgā āhuatanga kei a mātou | What we offerThe University of Auckland is New Zealand’s leading university and maintains significant computational, laboratory and analytic facilities. Auckland itself is frequently rated as one of the world’s most liveable cities.The University is committed to providing an excellent working environment with flexible employment practices.In addition, we also offer career development programmes, discounted car parking, a generous parental leave allowance, childcare, and a number of other discounts on internal and external services. For more information, please visit Staff Benefits.Me pēhea te tuku tono | How to applyApplications must be submitted online, by the closing date of 1 July 2026 to be considered. Please include your cover letter and your CV highlighting how you meet the skills and experiences detailed above.Please reach out to Deborah Clifford, via [email protected] , for a confidential conversation. Please note we are happy to answer your questions, but we do not accept applications by email.   #LI-DNI

We are looking to recruit a postdoctoral researcher to join the growing Lab for Lab for Uncertainty in Data and Decision Making (LUCID) in the School of Computer Science. Applicants should have a relevant background in information extraction, entity resolution/entity linking, machine learning, uncertainty modelling, explainable AI, or a closely related area, with a PhD (or near completion) in computer science, artificial intelligence, data science, computational linguistics, or another relevant subject area with the required expertise.You, the successful applicant, will contribute to interdisciplinary research on uncertainty-aware entity resolution and explainable decision support. Specifically, you will work on methods for capturing, representing, propagating and aggregating multiple forms of uncertainty in entity resolution pipelines, including uncertainty associated with entity spans, entity types, contextual evidence, model support, source provenance and cross-source conflict.You will be part of the project EXERCURA: Explainable Entity Resolution via Multi-Component Uncertainty and Robust Aggregation, between the University of Nottingham, The Alan Turing Institute. As a member of the research team, you will be based within the LUCID research group at the University of Nottingham’s Jubilee Campus, with opportunities for collaboration with relevant partners and stakeholders.The work has a strong focus on developing explainable and uncertainty-aware AI systems for linking mentions to entities under ambiguity, while building on advances in natural language processing, representation learning, information fusion, robust aggregation and human-centred decision support. A key part of the project is to develop approaches that help users understand not only which entity has been linked, but also why a link was made, why alternatives may remain plausible, or why a case may need to be deferred for analyst review. You will have expertise in areas such as natural language processing, entity resolution/entity linking, information extraction, machine learning, representation learning, uncertainty estimation, explainable AI, or information aggregation/fusion, together with strong programming skills. You will be keen to innovate and excited to learn more about areas which you may not yet be familiar with, including from other disciplines, integrating insights into your research and associated publications. A prior background in interdisciplinary research, human-centred AI, decision support, or analyst-facing systems would be desirable but is not essential.Your key activities will be to design and implement methods for decomposing and capturing uncertainty signals in entity resolution. You will also develop and evaluate uncertainty-aware aggregation approaches, including methods that combine evidence-worth and source-worth to support robust and inspectable entity linking. The project will include software implementation, experimental evaluation, contribution to project deliverables, and the writing-up and dissemination of research outputs, including presentation at conferences as appropriate. You will be mentored throughout the duration of the role, and the research team will support you in developing your research career.The project is not currently classified and formal security clearance is not required for this role at this stage. The successful applicant may be required to complete a Personal Particulars – Research Workers form and meet the UK Government Baseline Personnel Security Standard. Future project activities may be subject to additional security screening or formal security clearance requirements.What nextFurther information is available in the role profile. To apply for this vacancy please click ‘Apply Now’ to complete your details.To find out more about what we can offer you, follow the link to our benefits websiteThis is a Full Time, Fixed-Term post until 31/03/2027. Informal enquiries may be addressed to Dr Direnc Pekaslan at [email protected]. Please note that applications sent directly to this email address will not be accepted. Closing Date: 23 Jul 2026 Category: Research and Teaching (R&T)

Finance AnalystBailrigg Campus (Hybrid Working Available)Lancaster University are looking for a passionate, experienced and proactive Finance Analyst to join the Financial Planning & Analysis (FP&A) Team.Lancaster University is an established, thriving UK university with a world-class reputation for excellence in research, teaching and engagement. Lancaster is consistently ranked in the top universities in all three major UK league tables and continues to build a growing reputation both nationally and internationally.This Finance Analyst role will work closely with the Finance Partner in providing key budget holders with financial support, budget management, business planning, and performance reporting.You will have experience and achievement in a financial support setting. You will be a strong team player with excellent communication skills, building trusted relationships and working closely with members of the FP&A team and with other colleagues within the University. You will likely be actively studying towards an AAT qualification, or equivalent.Lancaster University offers a competitive salary, generous leave entitlement, professional development opportunities, and family-friendly policies. We are committed to equality of opportunity and welcome applications from all sections of the community.Applicants must meet all the essential criteria on the Person Specification to be considered for interview. The potential for a job-share opportunity may be considered for internal candidates, in exceptional circumstances.If you have any questions or would like an informal discussion about the role, please contact John Parkinson, Finance Partner ([email protected]). Closing Date: 26 Jul 2026 Department: Support - Administrative Salary: £26,707 to £30,378 (Full-Time/Fixed-Term)