Christina Ekegren

This PhD stipend scholarship at Monash University’s School of Primary and Allied Health Care offers an outstanding opportunity for talented candidates to undertake research in hospital-associated functional decline and deconditioning in older adults. The position is based at the Peninsula campus and forms part of the NHMRC-funded 'Smart Ward PREDICT' project, situated within the Rehabilitation, Ageing and Independent Living (RAIL) Research Centre. The project leverages data from the National Centre for Healthy Ageing Smart Ward and Healthy Ageing Data Platform, focusing on the loss of independence in activities of daily living (ADLs) during hospitalisation and its significant impacts, including increased risk of re-admission, premature entry to residential aged care, and mortality. The research aims to build the evidence base for hospital-associated functional decline and deconditioning, improving preventive efforts before, during, and after hospitalisation. Specific research questions include evaluating published interventions, identifying prevalence, risk factors, economic costs, and consequences, and exploring the predictive value of movement patterns detected by sensor technologies in hospitalised older adults. The successful candidate will be supported by a multidisciplinary project team with expertise in ageing, healthcare, biostatistics, and digital health. The main supervisor is Associate Professor Christina Ekegren, whose academic profile can be found at Monash University. Additional supervisors will be confirmed. The position offers a PhD annual stipend of $37,145 per annum (2026 rate) for 3.5 years, indexed annually. Further support includes the School of Primary and Allied Health Care HDR Support Fund (up to $4,000) and the Monash Graduate Research Travel Grant. The project is funded by the National Health and Medical Research Council (NHMRC). Applicants must meet Monash University PhD entry requirements, including citizenship or permanent residency, a four-year bachelor’s degree with research thesis/project and First Class Honours Division A, or a master’s degree with research thesis/project (minimum 25% of one year full-time study) and First Class Honours Division A, or equivalent qualifications/experience. Preferred candidates will have a background in epidemiology/biostatistics and a relevant clinical discipline such as nursing, medicine, or allied health, and be available to commence full-time in Q4 2026. The application process involves two stages: first, submit an Expression of Interest (EOI) to Dr Michelle Shannon, including a cover letter, CV, academic transcripts, and referee contact details. Successful candidates will then be invited to submit a full PhD candidature application. The deadline for applications is Sunday, 28 June 2026, 11:55pm AEST. For further information, refer to the Monash jobs website and the supervisor’s academic profile. This opportunity is ideal for candidates interested in clinical research, ageing, rehabilitation, and public health, with strong support for professional development and collaborative research activities.

This PhD stipend scholarship at Monash University’s School of Primary and Allied Health Care offers an exciting opportunity to advance the care and safety of hospitalised older adults through the use of advanced localisation and motion-based sensor technologies. The project is based at the Peninsula campus and forms part of the NHMRC-funded ‘Smart Ward PREDICT’ initiative, leveraging data from the National Centre for Healthy Ageing Smart Ward and Healthy Ageing Data Platform. The successful candidate will join the Rehabilitation, Ageing and Independent Living (RAIL) Research Centre and be supported by a multidisciplinary team with expertise in ageing, healthcare, biostatistics, and digital health. Supervised by Associate Professor Christina Ekegren, the PhD candidate will investigate the real-world acceptability, validity, and clinical relevance of emerging sensor technologies such as radar, RFID, and Bluetooth in hospital, aged care, and home settings. The project aims to build an evidence base to guide clinical policy and practice, addressing key research questions including the psychometric properties and impact of these technologies, algorithm development and technical validation for movement and falls detection, and the use of machine learning to predict adverse outcomes like delirium and behaviours of concern. Perspectives of patients and staff on the acceptability and clinical utility of these technologies will also be explored. The scholarship provides a generous annual stipend of $37,145 (2026 rate) for 3.5 years, indexed annually, with additional support for project resources and conference presentations through the School of Primary and Allied Health Care HDR Support Fund (up to $4,000) and the Monash Graduate Research Travel Grant. The candidate will participate in collaborative activities with the project team, enhancing their skills and capabilities in a dynamic research environment. Applicants must meet Monash University’s PhD entry requirements, including citizenship or permanent residency in Australia or New Zealand, and hold a four-year bachelor’s degree with a research thesis (First Class Honours Division A) or a master’s degree with a research thesis (minimum 25% of one year full-time study, First Class Honours Division A), or equivalent qualifications and relevant professional or research experience. Preferred candidates will have a background in sensor technology, psychometrics, and a relevant clinical discipline such as nursing, medicine, or allied health, and be available to commence full-time in Q4 2026. The application process involves two stages: first, submit an Expression of Interest (EOI) to Dr Michelle Shannon with a cover letter, CV, academic transcripts, and referee contact details. Successful EOI candidates will be invited to submit a full PhD application. The deadline for applications is Sunday, 28 June 2026, 11:55pm AEST. For further information, refer to the supervisor’s academic profile and the Monash University job application portal. This position is ideal for candidates passionate about digital health, sensor technology, and improving outcomes for older adults in hospital settings. The project offers a unique blend of technical, clinical, and collaborative research, supported by a leading Australian university and a diverse, multidisciplinary team.