{"meta":{"requested-page-number":1,"requested-page-size":20,"actual-page-size":20,"total-pages":1733,"total-size":34657,"search-description":null,"sort-by":""},"links":{"self":"http://dataportal.arc.gov.au/RGS/API/grants?page%5Bnumber%5D=1&page%5Bsize%5D=20","first":"http://dataportal.arc.gov.au/RGS/API/grants?page%5Bnumber%5D=1&page%5Bsize%5D=20","last":"http://dataportal.arc.gov.au/RGS/API/grants?page%5Bnumber%5D=1733&page%5Bsize%5D=20","prev":"http://dataportal.arc.gov.au/RGS/API/grants?page%5Bnumber%5D=1&page%5Bsize%5D=20","next":"http://dataportal.arc.gov.au/RGS/API/grants?page%5Bnumber%5D=2&page%5Bsize%5D=20"},"data":[{"type":"grants","id":"ID260100164","attributes":{"code":"ID260100164","program-name":"National Intelligence Grants","scheme-name":"National Intelligence Discovery Grants (NIDG)","funding-commencement-year":2026,"scheme-information":{"scheme-code":"ID  ","program":"National Intelligence Grants","submission-year":2026,"round-number":1,"scheme-round":"ID26 Round 1"},"grantee":"The University of New South Wales","grant-funder":"Office of National Intelligence","grant-title":"Unlocking the potential of biopolymers for mechanical energy harvesting","grant-summary":"This project aims to optimize biopolymer mechanical-to-electrical energy conversion by engineering polymer structures to decouple dipole-ion mechanisms while developing measurement methods to isolate individual electro-mechanical contributions. The significance lies in creating energy harvesters with optimised electrical output, while being both conformable to biological tissue and biocompatible. This has the potential to power covert wearable devices indefinitely, eliminating batteries and enabling persistent intelligence-gathering and health monitoring through continuous power generation from breathing, walking, and physiological processes.","lead-investigator":"A/Prof Damia Mawad","grant-value":784901.00,"grant-status":"Active","primary-field-of-research":"3403 - Macromolecular and Materials Chemistry","anticipated-end-date":"2029-06-30","investigators":"A/Prof Damia Mawad; A/Prof John Daniels","grant-priorities":[{"priority-type":"The Intelligence Challenges","priority-name":"Emerging biological science challenges"},{"priority-type":"The Intelligence Challenges","priority-name":"Emerging material science challenges"}]},"links":{"self":"http://dataportal.arc.gov.au/RGS/API/grants/ID260100164"}},{"type":"grants","id":"ID260100375","attributes":{"code":"ID260100375","program-name":"National Intelligence Grants","scheme-name":"National Intelligence Discovery Grants (NIDG)","funding-commencement-year":2026,"scheme-information":{"scheme-code":"ID  ","program":"National Intelligence Grants","submission-year":2026,"round-number":1,"scheme-round":"ID26 Round 1"},"grantee":"The Australian National University","grant-funder":"Office of National Intelligence","grant-title":"Biological Language Models in Threat Detection and Response","grant-summary":"This project proposes researching artificial intelligence tools in synthetic biology to jointly identify harmful biological sequences that are invisible to current detection methods, and rapidly generate prophylactics that can neutralise sudden or emerging biological hazards.\nAdvances in artificial intelligence are revolutionising how biology is studied and engineered. Generative AI can create new biological agents (such as proteins and viruses) that offer solutions to challenges in health and industry. However, the same technology can also be used maliciously to create novel and potent toxins and pathogens.\nThe project will deliver AI-enabled systems capable of detecting harmful artificial biological agents and designing rapid interventions to counteract them.\nThis work will address a critical vulnerability in Australian security by strengthening national capabilities in biological threat detection and response, ultimately protecting public health and the economy.","lead-investigator":"Dr Matthew Spence","grant-value":793320.00,"grant-status":"Active","primary-field-of-research":"3102 - Bioinformatics and Computational Biology","anticipated-end-date":"2029-06-30","investigators":"Dr Matthew Spence; Prof Eric Stone; Prof Colin Jackson","grant-priorities":[{"priority-type":"The Intelligence Challenges","priority-name":"Data-driven and real-time analytical challenges"},{"priority-type":"The Intelligence Challenges","priority-name":"Emerging biological science challenges"}]},"links":{"self":"http://dataportal.arc.gov.au/RGS/API/grants/ID260100375"}},{"type":"grants","id":"ID260100366","attributes":{"code":"ID260100366","program-name":"National Intelligence Grants","scheme-name":"National Intelligence Discovery Grants (NIDG)","funding-commencement-year":2026,"scheme-information":{"scheme-code":"ID  ","program":"National Intelligence Grants","submission-year":2026,"round-number":1,"scheme-round":"ID26 Round 1"},"grantee":"Griffith University","grant-funder":"Office of National Intelligence","grant-title":"Understanding new threats of extremism in Australia: Causes, consequences and solutions","grant-summary":"This project examines the threat of sovereign citizen (SovCit) extremism in Australia—a movement identified by the Australian Security Intelligence Organisation as a growing national security concern. Despite increasing incidents of SovCit-linked violence, little empirical research exists into what drives this ideology or how to mitigate its risks. This project aims to: identify the prevalence of this ideology; distinguish the factors driving SovCit beliefs from those triggering violence; test a grievance-based theoretical framework; and inform intervention strategies for authorities. Using police bodyworn camera footage, a national survey, and targeted sampling and analysis of SovCit adherents, the project will produce new insights into the drivers of SovCit extremism and practical strategies to help authorities identify, manage, and mitigate threats. Outcomes will inform practical, evidence-based tools to protect public officials and improve responses to anti-government extremism.","lead-investigator":"Prof Kristina Murphy","grant-value":799801.00,"grant-status":"Active","primary-field-of-research":"4402 - Criminology","anticipated-end-date":"2029-06-30","investigators":"Prof Kristina Murphy; A/Prof Keiran Hardy","grant-priorities":[{"priority-type":"The Intelligence Challenges","priority-name":"Human behaviour and influence challenges"}]},"links":{"self":"http://dataportal.arc.gov.au/RGS/API/grants/ID260100366"}},{"type":"grants","id":"ID260100603","attributes":{"code":"ID260100603","program-name":"National Intelligence Grants","scheme-name":"National Intelligence Discovery Grants (NIDG)","funding-commencement-year":2026,"scheme-information":{"scheme-code":"ID  ","program":"National Intelligence Grants","submission-year":2026,"round-number":1,"scheme-round":"ID26 Round 1"},"grantee":"Monash University","grant-funder":"Office of National Intelligence","grant-title":"Microscale probes for magnetic detection of brain activity","grant-summary":"This project aims to develop micro-scale probes for use in the brain to sense the extremely small magnetic fields resulting from the currents flowing along nerve cells. In contrast to electrical probes that directly sense the voltage changes generated by nerve cells, analogous probes for sensing magnetic fields are much less developed. The main reason is the weakness of the magnetic fields produced by neural activity requires very sensitive magnetic detectors, which can only be realised at the micro-scale by quantum sensors. The probe to be developed will utilse a quantum sensor based on optically detectable defects in diamond that are sensitive to magnetic fields. Such a probe should allow the study of magnetism in brain activity at the spatial scale of microns. Measuring localised magnetic fields in the brain represents a new approach to interrogating brain function, diagnosing neurological disorders, and for brain-machine interfaces.","lead-investigator":"Prof Kristian Helmerson","grant-value":791406.00,"grant-status":"Active","primary-field-of-research":"5108 - Quantum Physics","anticipated-end-date":"2029-08-04","investigators":"Prof Kristian Helmerson; Dr Haoran Ren; Prof Yan Wong; Dr Michael Barson","grant-priorities":[{"priority-type":"The Intelligence Challenges","priority-name":"Emerging biological science challenges"},{"priority-type":"The Intelligence Challenges","priority-name":"Emerging material science challenges"}]},"links":{"self":"http://dataportal.arc.gov.au/RGS/API/grants/ID260100603"}},{"type":"grants","id":"ID260100207","attributes":{"code":"ID260100207","program-name":"National Intelligence Grants","scheme-name":"National Intelligence Discovery Grants (NIDG)","funding-commencement-year":2026,"scheme-information":{"scheme-code":"ID  ","program":"National Intelligence Grants","submission-year":2026,"round-number":1,"scheme-round":"ID26 Round 1"},"grantee":"The University of Western Australia","grant-funder":"Office of National Intelligence","grant-title":"Culture-Aligned Influence: Understanding Social Influence Across Diverse Populations","grant-summary":"This project will examine how cultural differences shape the success or failure of social influence campaigns. Building on our successful NISDRG grant, which focused on social influence in Western populations—published in the prestigious Journal of Personality and Social Psychology—this project extends that work to non-Western populations. Messages that are persuasive in one context can fail, spread poorly, or even backfire in another. Large language models (LLMs), increasingly used to generate campaign messages, are similarly biased toward Western perspectives. This project will test whether culturally aligned messages are more effective at influencing non-Western audiences and whether new or adapted LLMs can generate such messages. The expected outcome is a method for creating culturally informed campaigns that are more effective and reliable across diverse populations, supporting the national intelligence community in avoiding cultural missteps and unintended effects.","lead-investigator":"A/Prof Nicolas Fay","grant-value":792888.00,"grant-status":"Active","primary-field-of-research":"4602 - Artificial Intelligence","anticipated-end-date":"2029-06-30","investigators":"A/Prof Nicolas Fay; Dr Mehwish Nasim; Dr Keith Ransom; Prof Yoshihisa Kashima","grant-priorities":[{"priority-type":"The Intelligence Challenges","priority-name":"Human behaviour and influence challenges"}]},"links":{"self":"http://dataportal.arc.gov.au/RGS/API/grants/ID260100207"}},{"type":"grants","id":"ID260100027","attributes":{"code":"ID260100027","program-name":"National Intelligence Grants","scheme-name":"National Intelligence Discovery Grants (NIDG)","funding-commencement-year":2026,"scheme-information":{"scheme-code":"ID  ","program":"National Intelligence Grants","submission-year":2026,"round-number":1,"scheme-round":"ID26 Round 1"},"grantee":"The University of Newcastle","grant-funder":"Office of National Intelligence","grant-title":"Hacking the Hackers: Understanding Cyber Attacker Cognition","grant-summary":"This project aims to understand how cyber attackers think and make decisions, with the goal of improving Australia’s cybersecurity. Instead of just blocking hackers, the research will use covertly-measured data to study their behaviour and expose and understand weaknesses in their decision-making. The team will build new mathematical models to understand, predict, and exploit cognitive biases in attackers. The expected outcomes include a process-level theory of attacker behaviour which can generate precise and actionable predictions. This will provide new ways to disrupt cyber threats, and tools to help protect critical systems. The project will train young researchers in cutting-edge methods and strengthen Australia’s links with national security agencies. The project offers high return on investment by leveraging US research activities. ","lead-investigator":"Prof Scott Brown","grant-value":783409.00,"grant-status":"Active","primary-field-of-research":"5204 - Cognitive and Computational Psychology","anticipated-end-date":"2029-08-31","investigators":"Prof Scott Brown; Prof Ami Eidels","grant-priorities":[{"priority-type":"The Intelligence Challenges","priority-name":"Covert collection challenges"},{"priority-type":"The Intelligence Challenges","priority-name":"Cyber security, protective security and physical security challenges"},{"priority-type":"The Intelligence Challenges","priority-name":"Human behaviour and influence challenges"}]},"links":{"self":"http://dataportal.arc.gov.au/RGS/API/grants/ID260100027"}},{"type":"grants","id":"ID260100556","attributes":{"code":"ID260100556","program-name":"National Intelligence Grants","scheme-name":"National Intelligence Discovery Grants (NIDG)","funding-commencement-year":2026,"scheme-information":{"scheme-code":"ID  ","program":"National Intelligence Grants","submission-year":2026,"round-number":1,"scheme-round":"ID26 Round 1"},"grantee":"The University of Queensland","grant-funder":"Office of National Intelligence","grant-title":"Mapping Religious and Sacred Ideals in Australian Pseudolaw Narratives","grant-summary":"This project aims to analyse how Australian pseudolaw and Sovereign Citizen disinformation, which has potential to spur violence and strain civil justice systems, employs narratives featuring religious and sacred values. Using internet-mediated ethnography and qualitative narrative analysis, it will identify the chief online sources of this disinformation and its most prominent Australian evangelists. Its goal will be to analyse such disinformation’s overarching themes, interaction patterns, and rhetoric, especially in relation to religion and sacred values; tracing how narratives support authority structures, promote antigovernment attitudes, and act as recruitment pathways. The project aims to identify exemplar narratives, detailing their plotlines and how they tend to cohere around shared religious ideas and sacred ideals. Altogether, the project will generate ethnographic and narrative analytical maps that can be leveraged to counter such disinformation as well as similar threats.","lead-investigator":"A/Prof Thomas Aechtner","grant-value":768640.00,"grant-status":"Active","primary-field-of-research":"5004 - Religious Studies","anticipated-end-date":"2029-11-29","investigators":"A/Prof Thomas Aechtner; Dr Laura Ferris; Dr Charles O'Quinn","grant-priorities":[{"priority-type":"The Intelligence Challenges","priority-name":"Human behaviour and influence challenges"}]},"links":{"self":"http://dataportal.arc.gov.au/RGS/API/grants/ID260100556"}},{"type":"grants","id":"ID260100177","attributes":{"code":"ID260100177","program-name":"National Intelligence Grants","scheme-name":"National Intelligence Discovery Grants (NIDG)","funding-commencement-year":2026,"scheme-information":{"scheme-code":"ID  ","program":"National Intelligence Grants","submission-year":2026,"round-number":1,"scheme-round":"ID26 Round 1"},"grantee":"The University of Queensland","grant-funder":"Office of National Intelligence","grant-title":"Interactional data models for next generation topic and sentiment analytics","grant-summary":"Text analytics can be used to assess and evaluate what people are talking about (topic) and how they feel about it (sentiment, stance). However, current computational approaches for analysing topic and sentiment are limited by under-specification and ad hoc incorporation of interactional context. The aim of this project is to develop formal interactional data models that address the dialogic properties of communication, which can then be used as a blueprint for re-engineering topic and sentiment analytics. Grounded in an approach to data modelling as research practice, this project expects to develop novel data models for analysing topic and sentiment in common modes of communication across different interactional contexts. These formal interactional models can then provide the basis for engineering next-generation interactional topic and sentiment analytics that fully leverage the affordances of data-driven, real-time analytics for addressing human behaviour and influence challenges.","lead-investigator":"Prof Michael Haugh","grant-value":799979.00,"grant-status":"Active","primary-field-of-research":"4602 - Artificial Intelligence","anticipated-end-date":"2029-10-05","investigators":"Prof Michael Haugh; Dr Samuel Hames; Prof Charles Kemp","grant-priorities":[{"priority-type":"The Intelligence Challenges","priority-name":"Data-driven and real-time analytical challenges"},{"priority-type":"The Intelligence Challenges","priority-name":"Human behaviour and influence challenges"}]},"links":{"self":"http://dataportal.arc.gov.au/RGS/API/grants/ID260100177"}},{"type":"grants","id":"ID260100231","attributes":{"code":"ID260100231","program-name":"National Intelligence Grants","scheme-name":"National Intelligence Discovery Grants (NIDG)","funding-commencement-year":2026,"scheme-information":{"scheme-code":"ID  ","program":"National Intelligence Grants","submission-year":2026,"round-number":1,"scheme-round":"ID26 Round 1"},"grantee":"Adelaide University","grant-funder":"Office of National Intelligence","grant-title":"Missed signals in the escalation to extremist violence: Revealing the connection between extremism, child sexual exploitation and domestic violence","grant-summary":"Australia faces a critical blind spot: the relationship between child sexual exploitation (CSE), domestic and sexual violence (DSV) and extremist violence. Recent poly-offending – now known as sadistic online exploitation (SOE) – suggests an evolving extremism environment; this project aims to deliver world-first evidence on these connections. A large-scale survey will measure behavioural and psychological profiles of SOE, including variation by ideology and age, while analyses of dark web forums and encrypted platforms will measure interactions, behaviours and pathways into SOE extremist networks. Importantly, these methods will allow analysis of self-identified extremists who have, as yet, avoided apprehension, allowing insights into undetected offending and escalation. Expected outcomes include behavioural and psychological risk profiles, an interactive findings Dashboard for NIC and police use, and an operational handbook synthesising insights and recommended actions.","lead-investigator":"A/Prof Timothy Cubitt","grant-value":788774.00,"grant-status":"Active","primary-field-of-research":"4402 - Criminology","anticipated-end-date":"2029-06-30","investigators":"A/Prof Timothy Cubitt; Prof Russell Brewer; Dr Hayley Boxall; Dr Katie Logos","grant-priorities":[{"priority-type":"The Intelligence Challenges","priority-name":"Data-driven and real-time analytical challenges"},{"priority-type":"The Intelligence Challenges","priority-name":"Human behaviour and influence challenges"},{"priority-type":"The Intelligence Challenges","priority-name":"Situation awareness and multi-source assessment challenges"}]},"links":{"self":"http://dataportal.arc.gov.au/RGS/API/grants/ID260100231"}},{"type":"grants","id":"ID260100109","attributes":{"code":"ID260100109","program-name":"National Intelligence Grants","scheme-name":"National Intelligence Discovery Grants (NIDG)","funding-commencement-year":2026,"scheme-information":{"scheme-code":"ID  ","program":"National Intelligence Grants","submission-year":2026,"round-number":1,"scheme-round":"ID26 Round 1"},"grantee":"RMIT University","grant-funder":"Office of National Intelligence","grant-title":"Piezoelectric Gels for Battery-Free Wearable Biometric Monitoring and Covert Data Collection","grant-summary":"This project aims to develop non-toxic, flexible materials that generate electrical energy in response to deformation combined with innovative 3D-printed titanium diamond antennas for wireless tranmission of the generated energy. The project is significant as it should generate new knowledge into energy harvesting materials that contribute to the paradigm change required to reduce our reliance on heavy, short lived and easily damaged batteries. Expected outcomes of this project include the creation of battery-free, wireless energy harvesting materials that convert body movement into power for wearable devices such as biometric sensors and covert intelligence gathering devices. These materials should be developed for the benefit of in-field intelligence officers, providing lightweight, robust materials to power wearables in remote and inhospitable locations. Additional benefits may include providing power to implantable medical devices, biosensors and tissue engineering devices.    ","lead-investigator":"Dr Nicholas Reynolds","grant-value":799812.00,"grant-status":"Active","primary-field-of-research":"3106 - Industrial Biotechnology","anticipated-end-date":"2029-06-30","investigators":"Dr Nicholas Reynolds; Dr Peter Sherrell; Prof Kate Fox; Dr Arman Ahnood; Dr Simon Cook","grant-priorities":[{"priority-type":"The Intelligence Challenges","priority-name":"Covert collection challenges"},{"priority-type":"The Intelligence Challenges","priority-name":"Emerging material science challenges"}]},"links":{"self":"http://dataportal.arc.gov.au/RGS/API/grants/ID260100109"}},{"type":"grants","id":"LP250201134","attributes":{"code":"LP250201134","program-name":"Linkage","scheme-name":"Linkage Projects","funding-commencement-year":2026,"scheme-information":{"scheme-code":"LP  ","program":"Linkage","submission-year":2025,"round-number":2,"scheme-round":"LP25 Round 2"},"grantee":"The University of Melbourne","grant-funder":"Australian Research Council","grant-title":"Value chain analysis and governance for nature positive organisations","grant-summary":"This project aims to investigate how businesses can understand, report, and reduce impacts on nature. The project will develop a biodiversity impact workflow for organisations to evaluate their nature-related impacts and opportunities, both direct and in supply chains, and characterise transformation pathways for achieving nature positive outcomes. Expected outcomes include new metrics and tools for identifying the nature-related impacts of supply chains, and governance pathways for businesses to become nature positive. This will provide significant benefits to society and businesses by supporting high-integrity certification, transformation of business practices, enhancing competitiveness, and alignment with global biodiversity goals.","lead-investigator":"Prof Brendan Wintle","grant-value":859198.00,"grant-status":"Active","primary-field-of-research":"4104 - Environmental Management","anticipated-end-date":"2029-12-31","investigators":"Prof Brendan Wintle; Prof Sarah Bekessy; Dr William Geary; Prof Vikram Bhakoo; A/Prof Kwok Hung Lau; Dr Matthew Selinske; Dr Ella Kelly; Dr Sasha Courville","grant-priorities":[]},"links":{"self":"http://dataportal.arc.gov.au/RGS/API/grants/LP250201134"}},{"type":"grants","id":"LP250201130","attributes":{"code":"LP250201130","program-name":"Linkage","scheme-name":"Linkage Projects","funding-commencement-year":2026,"scheme-information":{"scheme-code":"LP  ","program":"Linkage","submission-year":2025,"round-number":2,"scheme-round":"LP25 Round 2"},"grantee":"The University of Melbourne","grant-funder":"Australian Research Council","grant-title":"Advanced Optical Interlayers for High-Performance Energy-Harvesting Windows","grant-summary":"The world is experiencing climate change due to human activities. This project aims to design, model, construct and test new “power windows” which will be able to generate solar power, while still functioning as windows in buildings. The significance is that such windows could dramatically reduce energy consumption and hence greenhouse gases by enabling city skyscrapers, homes, factories and agricultural greenhouses to generate their own electricity. The expected outcomes of this project will be an advanced, Australian designed and manufactured window, which can be incorporated into buildings worldwide. The key benefits will be the creation of high-value Australian jobs and export opportunities in the green economy.","lead-investigator":"Prof Paul Mulvaney","grant-value":283190.00,"grant-status":"Active","primary-field-of-research":"4009 - Electronics, Sensors and Digital Hardware","anticipated-end-date":"2028-12-31","investigators":"Prof Paul Mulvaney; A/Prof James Bullock; Dr Mikhail Vasiliev","grant-priorities":[]},"links":{"self":"http://dataportal.arc.gov.au/RGS/API/grants/LP250201130"}},{"type":"grants","id":"LP250201126","attributes":{"code":"LP250201126","program-name":"Linkage","scheme-name":"Linkage Projects","funding-commencement-year":2026,"scheme-information":{"scheme-code":"LP  ","program":"Linkage","submission-year":2025,"round-number":2,"scheme-round":"LP25 Round 2"},"grantee":"Monash University","grant-funder":"Australian Research Council","grant-title":"Polymer Systems for Controlled Release of Biological Agents","grant-summary":"The project aims to develop polymer systems for the sustained release of biologicals that can be administered as a liquid and be cross-linked in situ. Unnatural amino acids will be incorporated into model biologicals via stop-codon reassignment, and then used to convert the biologicals into polymerizable macromonomers. The macromonomers will be capable of undergoing quantitative, in situ crosslinking via innovative cycloaddition chemistry to form a functionalized gel with controlled rate of release of the biological agent and residue-free biodegradation. Novel polymers and compositions are anticipated from the program, providing a new patented platform technology with applications in the pharmaceutical and veterinary sectors.","lead-investigator":"A/Prof John Quinn","grant-value":656168.00,"grant-status":"Active","primary-field-of-research":"3403 - Macromolecular and Materials Chemistry","anticipated-end-date":"2028-12-31","investigators":"Dr Russell Tait; A/Prof John Quinn; Dr Daniel Priebbenow; A/Prof Angus Johnston; Dr Francesca Ercole; Prof Jonathan Crowston","grant-priorities":[]},"links":{"self":"http://dataportal.arc.gov.au/RGS/API/grants/LP250201126"}},{"type":"grants","id":"LP250201125","attributes":{"code":"LP250201125","program-name":"Linkage","scheme-name":"Linkage Projects","funding-commencement-year":2026,"scheme-information":{"scheme-code":"LP  ","program":"Linkage","submission-year":2025,"round-number":2,"scheme-round":"LP25 Round 2"},"grantee":"The University of New South Wales","grant-funder":"Australian Research Council","grant-title":"Resilient, Affordable and Ethical Regional Planning under Disaster Risk","grant-summary":"Our society faces increasing disaster risk and the urgent need for affordable housing. This project develops novel tools and evidence to support planning by addressing: (a) residential location decisions under disaster risk, (b) evacuation timing and destination choices, (c) real-world evacuation capacity estimation, (d) integrated models to evaluate economic resilience and investment trade-offs, and (e) ethics-aware planning that balances fairness, priority and cost-effectiveness. Combining virtual reality, behavioural modelling, traffic simulation and economic analysis, the project will help governments and emergency agencies deliver socially just, risk-informed and affordable regional strategies.","lead-investigator":"Prof Vinayak Dixit","grant-value":353071.00,"grant-status":"Active","primary-field-of-research":"3507 - Strategy, Management and Organisational Behaviour","anticipated-end-date":"2028-12-31","investigators":"Prof Vinayak Dixit; Dr Divya Jayakumar Nair; Prof Taha Hossein Rashidi; Mr David Lillo-Trynes; Dr Michelle Whitford; Mr Peter Cinque","grant-priorities":[]},"links":{"self":"http://dataportal.arc.gov.au/RGS/API/grants/LP250201125"}},{"type":"grants","id":"LP250201121","attributes":{"code":"LP250201121","program-name":"Linkage","scheme-name":"Linkage Projects","funding-commencement-year":2026,"scheme-information":{"scheme-code":"LP  ","program":"Linkage","submission-year":2025,"round-number":2,"scheme-round":"LP25 Round 2"},"grantee":"The University of Adelaide","grant-funder":"Australian Research Council","grant-title":"Novel Fluorescence Sensor for Selective Mining of Rare-Earth Elements","grant-summary":"This project aims to develop a new technique to detect rare-earth elements instantaneously in the field, in ways that unlock value in difficult-to-mine deposits, due to their grades, complexity, or environmental concerns. The expected outcomes of this project include the development and validation of the sensing technology on real-world samples, and increased knowledge of the mineralogy of Australian rare-earth reserves, particularly clays but including hard rock and mineral sands deposits, and rare-earth enriched tailings. Benefits are immediate for deposit assessment and mine planning, with subsequent commercialisation of the technology enabling sovereign uplift of a critical resource for the global need to transition to a green economy.","lead-investigator":"Prof Nigel Spooner","grant-value":896352.00,"grant-status":"Active","primary-field-of-research":"5102 - Atomic, Molecular and Optical Physics","anticipated-end-date":"2028-12-31","investigators":"Mr Rob Loughan; Prof Nigel Spooner; Prof William Skinner; Prof Carl Spandler; Dr Erik Schartner; Dr Laura Morrissey; Mr Rickie Pobjoy","grant-priorities":[]},"links":{"self":"http://dataportal.arc.gov.au/RGS/API/grants/LP250201121"}},{"type":"grants","id":"LP250201119","attributes":{"code":"LP250201119","program-name":"Linkage","scheme-name":"Linkage Projects","funding-commencement-year":2026,"scheme-information":{"scheme-code":"LP  ","program":"Linkage","submission-year":2025,"round-number":2,"scheme-round":"LP25 Round 2"},"grantee":"The University of Melbourne","grant-funder":"Australian Research Council","grant-title":"Advanced motion measurement technology for precision 3D joint movement","grant-summary":"Joint function is vital for healthy ageing, yet current methods for high-accuracy joint motion measurement rely on time-intensive and costly medical imaging and image processing, typically confined to specialist laboratories. This project aims to leverage low-radiation dose bi-plane x-ray imaging and advanced data-driven modelling to create a high throughput, accurate, robust and user-friendly precision motion analytics toolkit featuring an intuitive web-interface. This capability will allow joint motion assessment at scale by a non-expert. The technology could aid in future biomarker discovery for movement disorders, surgical planning, joint implant development, injury prevention, rehabilitation, and film and animation for education.","lead-investigator":"Prof David Ackland","grant-value":372207.00,"grant-status":"Active","primary-field-of-research":"4207 - Sports Science and Exercise","anticipated-end-date":"2028-12-31","investigators":"Prof David Ackland; Prof Richard Sinnott; Prof Saman Halgamuge; Dr Hans Gray; Mr Stuart Douglas","grant-priorities":[]},"links":{"self":"http://dataportal.arc.gov.au/RGS/API/grants/LP250201119"}},{"type":"grants","id":"LP250201116","attributes":{"code":"LP250201116","program-name":"Linkage","scheme-name":"Linkage Projects","funding-commencement-year":2026,"scheme-information":{"scheme-code":"LP  ","program":"Linkage","submission-year":2025,"round-number":2,"scheme-round":"LP25 Round 2"},"grantee":"Queensland University of Technology","grant-funder":"Australian Research Council","grant-title":"Assistive Robotics for Inclusive Employment","grant-summary":"People with intellectual disabilities (ID) often face challenges in finding employment. Even when they do, employers may struggle to find suitable work for them. There are currently no clear solutions to these issues. However, AI and assistive robotics show great promise in fostering the capabilities of people with ID. Our interdisciplinary research team will work with the disability sector using a co-design approach to explore how these technologies can help people with ID transition into sustainable employment and assist employers in creating suitable work tasks. This groundbreaking study aims to produce guidelines on using assistive robots to improve and maintain employment opportunities for people with ID and those employing them. ","lead-investigator":"A/Prof Laurianne Sitbon","grant-value":800810.00,"grant-status":"Active","primary-field-of-research":"4608 - Human-Centred Computing","anticipated-end-date":"2028-12-31","investigators":"A/Prof Laurianne Sitbon; Prof Margot Brereton; Dr Jessica Korte; A/Prof Sofia Mavropoulou; Prof Markus Rittenbruch; Mrs Kathleen Martin; Miss Chloe Haidenhofer; Mrs Amanda Leighton; Mr Mark Donachie","grant-priorities":[]},"links":{"self":"http://dataportal.arc.gov.au/RGS/API/grants/LP250201116"}},{"type":"grants","id":"LP250201108","attributes":{"code":"LP250201108","program-name":"Linkage","scheme-name":"Linkage Projects","funding-commencement-year":2026,"scheme-information":{"scheme-code":"LP  ","program":"Linkage","submission-year":2025,"round-number":2,"scheme-round":"LP25 Round 2"},"grantee":"RMIT University","grant-funder":"Australian Research Council","grant-title":"Explainable anomaly detection in heterogenous knowledge graphs\t","grant-summary":"This project aims to develop ground-breaking deep learning-based tools for anomaly detection in heterogeneous knowledge graphs, with a focus on payroll anomaly detection. It expects to generate new knowledge in modelling payroll records as heterogeneous graphs and applying AI techniques for accurate and interpretable anomaly detection. Expected outcomes include an automated payroll analytics system for real-time identification of anomalies, such as fraud and underpayments. This should provide significant benefits, such as improving financial data analysis, enhancing compliance with labour laws, and reducing legal and financial risks through early detection of payroll anomalies.","lead-investigator":"Dr Parham Moradi Dowlatabadi","grant-value":599951.00,"grant-status":"Active","primary-field-of-research":"4605 - Data Management and Data Science","anticipated-end-date":"2028-12-31","investigators":"Dr Parham Moradi Dowlatabadi; Prof Mahdi Jalili; Dr Hui Song; Prof Xinghuo Yu; A/Prof Wei Peng; Dr Mohammadreza Radmanesh","grant-priorities":[]},"links":{"self":"http://dataportal.arc.gov.au/RGS/API/grants/LP250201108"}},{"type":"grants","id":"LP250201101","attributes":{"code":"LP250201101","program-name":"Linkage","scheme-name":"Linkage Projects","funding-commencement-year":2026,"scheme-information":{"scheme-code":"LP  ","program":"Linkage","submission-year":2025,"round-number":2,"scheme-round":"LP25 Round 2"},"grantee":"The University of Melbourne","grant-funder":"Australian Research Council","grant-title":"Diamond Membranes for quantum applications ","grant-summary":"Diamond materials are ideal for quantum technologies and are leading the charge in the new wave of real-world quantum industries. The aim of this project is to develop a reliable source of quantum-active diamond membranes to be used as the basic building block for integrated optical quantum devices. We aim to create delta doped layers in the centre of the membranes which will then be processed by our partners, Quantum Transistors into quantum photonic chips.The expected outcome is the demonstration of a scalable  technology for the fabrication of a quantum processor that is widely accessible so  that society can  benefit from the immense potential of quantum technology.","lead-investigator":"Prof Steven Prawer","grant-value":685887.00,"grant-status":"Active","primary-field-of-research":"5108 - Quantum Physics","anticipated-end-date":"2028-12-31","investigators":"Prof Steven Prawer; Dr Moshe Tordjman; Dr Eilon Poem","grant-priorities":[]},"links":{"self":"http://dataportal.arc.gov.au/RGS/API/grants/LP250201101"}},{"type":"grants","id":"LP250201100","attributes":{"code":"LP250201100","program-name":"Linkage","scheme-name":"Linkage Projects","funding-commencement-year":2026,"scheme-information":{"scheme-code":"LP  ","program":"Linkage","submission-year":2025,"round-number":2,"scheme-round":"LP25 Round 2"},"grantee":"The University of Sydney","grant-funder":"Australian Research Council","grant-title":"Enabling VLA Assistive Robotics for the Future of Aged Care in Australia ","grant-summary":"This project aims to address the growing challenges in aged care by developing intelligent assistive robots that can see, listen, and act to support older Australians. It will create Australia’s first vision-language-action robotic system specifically designed for real-world aged care environments—where interactions are socially nuanced, physically sensitive, and built on trust. The project will deliver new AI and robotics capabilities, a reusable national data resource, and practical strategies for safe and adaptive robot behaviour. These advances will help improve the safety, dignity, and independence of older people, ease the burden on carers, and strengthen Australia’s leadership in ageing and care innovation.\n","lead-investigator":"A/Prof Chang Xu","grant-value":602648.00,"grant-status":"Active","primary-field-of-research":"4007 - Control Engineering, Mechatronics and Robotics","anticipated-end-date":"2028-12-31","investigators":"Ms Lynn Lan; A/Prof Chang Xu; Dr Daochang Liu; Dr Yunke Wang","grant-priorities":[]},"links":{"self":"http://dataportal.arc.gov.au/RGS/API/grants/LP250201100"}}]}