National University of Sciences and Technology

Role type:Full Time, Fixed Term for 2 years Faculty: Faculty of Science Department: School of Mathematics and Statistics Salary: Academic Level A.6 - $110.319 p.a. plus 17% super Lead innovative research, bridge quantum computing and omics and shape future of data analysis Apply now to advance the frontier of quantum biotechnology and integrative omics analysis Investing in you - benefits package including salary packaging, health and wellbeing programs, discounted services, and professional development opportunities. The University of Melbourne We take pride in our people, who all contribute to our mission to benefit society through the transformative impact of education and research. Discover more via our website. Your next career opportunity As a Postdoctoral Research Fellow in the L Cao lab, you'll spearhead method development at the exciting intersection of quantum computing and integrative omics. You'll have the opportunity to design, evaluate, and benchmark quantum-inspired computational approaches for analysing high-dimensional biological datasets. Working within the ARC Centre of Excellence in Quantum Biotechnologies (QUBIC), you'll contribute to groundbreaking research, collaborate with leading experts, and shape a new direction in quantum-omics integration. Your responsibilities will include: Lead Methodological Research: Develop innovative quantum-inspired algorithms for omics data analysis and multi-omics integration. Produce High-Impact Outputs: Deliver internationally competitive research through publications, conference presentations, and reproducible software. Foster Collaborations: Work closely with lab members and external partners to translate methodological advances into applied analyses and usable tools. Support Research Training: Co-supervise PhD and masters students, providing guidance on research design, analysis, and scientific communication. You may be a great fit if: You are a highly motivated researcher with a PhD in a relevant field, demonstrating expertise in both omics data analysis and quantum computing methods, with a passion for developing innovative computational approaches to solve complex biological problems. You may also: Have a PhD in statistics, computational biology, bioinformatics, computer science, quantum computing, or a closely related discipline. Demonstrate research capability in methods development relevant to quantum computing and omics. Possess experience in analysing high-dimensional biological data and applying quantum computing methods to data analysis. Have an active GitHub profile evidencing ongoing code development and contributions. For further information, please refer to the attached PD. What we offer you We offer the opportunity to be part of a vibrant community and enjoy a comprehensive range of benefits to support your success and sense of fulfilment, including: Supportive flexible work arrangements underpinned by our commitment to inclusion and well-being Progressive, considerate leave provisions to empower your work-life balance Salary packaging and access to a range of discounted services including Bupa health insurance Health and well-being services including a leading Employee Assistance Program For more information check out our benefits page! Your new team - "L Cao lab, Melbourne Integrative Genomics (MIG)"https://sites.research.unimelb.edu.au/integrative-genomics| https://lecao-lab.science.unimelb.edu.auL Cao lab is part of Melbourne Integrative Genomics (MIG), which has been established in 2017 and is an initiative to strengthen the involvement of statisticians in the advances being made in genomics and computational biology. MIG is an interdisciplinary research centre for the application of maths/stats/computing techniques to omics profiling data to help understand genotype-to-phenotype process in humans and other organisms. MIG includes 50+ members, and provides a wide range of opportunities for exciting research collaborations. The Parkville precinct has the greatest concentration of biological and medical research in Australia, and is among the greatest internationally.http://www.ms.unimelb.edu.auThe University of Melbourne's School of Mathematics and Statistics is one of Australia's leading mathematics and statistics schools. It has achieved this status through the high quality of its research and teaching programs. The School offers a wide range of subjects to undergraduate and postgraduate students and is involved in aspects of community life that impact on the interests of the School and the discipline. Be Yourself The University of Melbourne is an Equal Opportunity Employer and a child-safe organisation. We believe the diversity of our community enriches us all, and we are committed to creating an inclusive and fair workplace where everyone is valued, respected, and empowered to succeed. We welcome applicants from all backgrounds, identities, and experiences. Discover more about Diversity and Inclusion at UniMelb.We're committed to a barrier-free recruitment process and ongoing workplace support, providing reasonable adjustments throughout. We warmly encourage applications from people with disabilities. For assistance, please contact Kim Groizard on +61 3 9035 3218 or at hr-careers@unimelb.edu.au (subject: 'Recruitment Adjustments'). Contact details for other enquiries are located at the bottom of this page. Find more information for applicants requiring reasonable adjustments. Aboriginal and Torres Strait Islander Applicants We aspire to be the University of choice for Indigenous Australians. Our Indigenous strategy, Murmuk Djerring outlines our investment and support for Aboriginal and Torres Strait Islander staff and students. Indigenous applicants are encouraged to connect with "Korin-Korin" our Indigenous Employment & Development team at oied-hr@unimelb.edu.au for further information and support. Please note: Visa sponsorship is available for this position. A Working with Children Check (WWCC) is required for all positions. If successful, we'll guide you through the WWCC application process during onboarding and reimburse the cost. Join Us and unlock your career potential If this role is right for you, please apply with the following documents: Resume Cover Letter outlining your interest and experience The responses against the following Selection Criteria^ 1. PhD (or equivalent) in statistics, computational biology, bioinformatics, computer science, quantum computing, or a closely related discipline.2. Demonstrated research capability in methods development relevant to quantum computing and omics, evidenced through PhD work and associated outputs (for example publications, preprints, software, or technical reports), relative to opportunity.3. Demonstrated experience in analysing high-dimensional biological data, including appropriate preprocessing, quality control, and interpretation of results.4. Demonstrated experience applying or developing quantum computing methods relevant to data analysis (use of simulators acceptable), with clear understanding of limitations and appropriate evaluation.5. Demonstrated experience in version control on Github and an active GitHub profile evidencing ongoing code development and/or contributions Learn more about the application process, including tips and FAQs. For recruitment queries, email Anna at hr-careers@unimelb.edu.au. Include the Position Number and Job Title in the subject line. Please do not send applications to this email address. For job-specific queries, refer to the contact details in the Position Description. Applications close: 6 April 2026. 11:55 PM; Melbourne time zone. Position Description: JR-009383 Research Fellow Quantum Omics_PD.doc.docx JR-009383 Research Fellow Quantum Omics_PD.doc.pdf

About the role We are seeking an organised, detail‑oriented Clinical Research Data Integration Coordinator to work within the Cancer B‑cell Group on the CRUK Accelerator Programme “Early Cancer Research Initiative Network on Monoclonal B‑cell Lymphocytosis (ECRIN‑M3)”, led by Professor Francesco Forconi. You will be based in the School of Cancer Sciences, working closely with clinicians, scientists and data specialists to turn real‑world clinical information into clean, analysis‑ready research datasets from patients with leukaemia (e.g. Chronic lymphocytic leukaemia) and lymphomas (e.g. Follicular lymphoma). Your primary responsibility will be to systematically extract and curate clinical data from medical records (electronic patient record systems and, where applicable, paper notes) and integrate these data into research databases and linked study systems. You will play a central role in maintaining data quality, provenance, and completeness, ensuring robust, reproducible data flows from recruiting sites. For candidates with relevant interest and experience, there will be opportunities to contribute to analysis support (e.g., descriptive analyses, QC/consistency checks, basic survival summaries) and to develop/manage data pipelines (ETL, validation rules, automation, dashboards) in collaboration with the Clinical Informatics Research Unit (CIRU). What you’ll do Extract and abstract clinical variables from medical records into structured formats aligned to the protocol and data dictionaries. Curate, validate and reconcile clinical data with laboratory/biomarker and study datasets; resolve data queries with clinical teams. Integrate data into research repositories (e.g., BC Platforms) following SOPs, with clear documentation of provenance and versioning. Maintain data dictionaries, mapping tables and coding standards. Monitor completeness and quality; run routine QC/consistency checks; manage data corrections and audit trails. Liaise with recruiting sites, research nurses and international collaborators to support timely, accurate data flows. Adhere to information governance, confidentiality and research ethics requirements (e.g., GDPR, ethical approvals, data access controls). Contribute to analyses, dashboards and automated validation/ETL pipelines using SQL/Excel and/or R/Python, support simple visualisations and reports for investigators. About you Experience extracting/abstracting data from electronic medical records and/or clinical notes into structured datasets.  Meticulous attention to detail; comfortable navigating diverse clinical documentation.  Working knowledge of clinical terminologies/coding (e.g., ICD‑10, SNOMED CT, CTCAE); familiarity with haematology/oncology concepts is desirable.  Confident with Excel and at least one research data environment (e.g., SQL‑based tools, ALEA, BC Platforms, or similar data capture/warehouse systems).  Understanding of GDPR, confidentiality, research governance and data security in a clinical research setting.  Clear communicator who builds strong relationships with clinicians, research nurses and data specialists, and escalates appropriately when decisions or approvals are needed Self‑starter who takes ownership and progresses work independently, drawing on guidance and support from CIRU and the wider team when needed Proactive and solution‑focused, able to plan and prioritise workload, anticipate blockers, and propose pragmatic improvements to data capture, validation and workflows Desirable: basic scripting in R or Python; experience writing SQL for data cleaning/QC; exposure to survival/epidemiological concepts; experience with haematological malignancies or early cancer research About us A collaborative team spanning Cancer B‑cell immunology, genomics, molecular/cellular biology, bioinformatics and clinical informatics. The environment combines strong clinical engagement with modern data infrastructure to generate high‑quality real‑world datasets that inform patient care and translational research. We value diversity We welcome applications from all sections of the community and support flexible working where possible. If we receive a high volume of applications, we may close the vacancy early—please apply as soon as you are ready.

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.  Job Responsibilities Participate in and manage the research project with Principal Investigator (PI), Co-PI and the research team members to ensure all project deliverables are met.• Undertake these responsibilities in the project: i. Lead and support high quality publications to disseminate the applied research outcomes. ii. Plan, organize and carry out experiments and trials in the food pilot plant to achieve the objectives iii. Manage and complete the project by presenting the findings in conferences or meetings with industrial collaborator, submitting timely data & documents, and purchase chemicals or consumables. iv. Consolidate the data in order to generate sufficient scientific evidence for meetings slides and report in conferences. v. Engage and communicate with collaborators for progress meetings and report generation to meet the grantor's requirements. The candidate is to liaise and communicate with any internal or external stakeholders to ensure project deliverables are met and to perform any other adhoc duties assigned by Supervisor.  Job requirements Have relevant competence in the areas of protein chemistry, analytical chemistry for amino acid profiling, polyphenol profile analysis, SDS-PAGE, and protein hydrolysis. Have a degree in Food Science and Technology, or Analytical Chemistry. Possessing a Master's or PhD degree will be advantageous Experience and Knowledge of operating HPLC, MALDI-TOF and Q-TOF Mass spectrometry for protein sequencing, carbohydrate/Sugar analysis, and polyphenol identification. Previous experience as lab-in-charge or equipment-in-charge will be advantageous. Able to communicate with industrial collaborators to share key findings, seek supports, or conducting commercial trials. Carry out Risk Assessment, and ensure compliance with Work, Safety, and Health Regulations. Coordinate procurement and liaison with vendors/suppliers. Work independently, as well as within a team, to ensure proper operation and maintenance of equipment.