Round 2
Round 2 Projects
Metabolic Health Solutions
Novel Indirect Calorimeter Design
About
Metabolic Health Solutions (MHS) is an integrated medical technology and digital health company, commercialising low cost, metabolic measurement technology to clinically manage obesity, Type 2 Diabetes (T2DM) and other common metabolic disorders. MHS currently has CE, TGA and HSA Certification for its lead technology ECAL, and have early commercial activities in 8 Countries in Europe and Asia, including wholly owned and partner clinics.
Through our clinics and international research programmes we are building an evidence-based data set of the efficacy of indirect calorimetry in a clinical setting to better manage obesity and weight-related chronic disease. We are building this knowledge into a digital health platform ENABLE, that will allow health systems and individual practitioners to benefit from this evidence informed data led metabolic lifestyle approach. The large de-identified data footprint will use machine learning and expert analysis to support enhanced care and develop effective clinical and health economic models to reverse this global epidemic of metabolic disease.
Project
The project has had early feasibility assessment completed with a simple computational model and a preliminary test rig design developed.
In this project interns will work towards these aims:
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Refine the model & produce a 3D printed test rig to the existing design or as modified.
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Validate and improve the model using real human breath test data and compare to a final side by side measurement with our existing calorimeter.
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Work with the MHS business and technical teams to determine whether there is any physiological, clinical or commercial benefit to using this sensor as envisioned (report).
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Recommend the next steps to implement or not (report).
Learn More
ALEXANDRIA NIVELLE MEKANNA
Western Sydney University
School of Science
Skills: project management; research skills; communication; problem-solving; multitasking.
MOOMNA WAHEED
Macquarie University
Faculty of Medicine, Health & Human Sciences
Skills: software development with Python, Java, and MATLAB; working with Python libraries such as Scikit learn, numpy, pandas; Machine Learning and Deep Learning models using Pytorch, Keras, and tensor flow; computer vision algorithms (object detection, human action recognition); working with databases such as MySQL and Oracle.
JEROME LIAN
Curtin University
Curtin Medical School
Skills: self-reflection; process refinement; public speaking; information/ data gathering; digital literacy.
MIR ARMAN MIRZAAGHAIAN AMIRY
Western Sydney University
School of Engineering, Design and Building Environment
Skills: computational modelling of air flow in lung and respiratory system; programming; critical thinking; time management; research and literature review.
North Metropolitan Health Service
Sir Charles Gairdner Hospital
Predictive AI Model for binding of complex molecules and cell receptors: Implications for discovery of novel antigens in autoimmune disease
About
The North Metropolitan Health Service (NMHS) is one of Western Australia’s public health jurisdictions. It encompasses the Sir Charles Gairdner Hospital (SCGH), a 600 bed tertiary medical facility situated on the QEII Medical Centre campus which provides the principal collaborative medical environment for UWA. A core value of NMHS is innovation, and the service extensively supports research activity with many clinical trials, basic science developments, medical device and public health practice innovations supported on site. The Department of Radiation Oncology at SCGH has particularly supported research and innovation and hosts the Medical Physics Research Group from UWA. This technology-focused department enables research into data science applications and has supported the efforts of the Medical Physics group to specialise in machine learning and artificial intelligence (ML/AI) methods. These efforts have seen the undertaking of new investigations to apply the power of ML/AI to basic and clinical investigations.
Project
Accurate prediction of the interactions between molecules and cell features has profound implications for immunology, personalized medicine, and drug discovery. Such predictions can lead to the identification of potential vaccines, improved cancer immunotherapies, and a deeper understanding of autoimmune diseases. Additionally, precise prediction models can reduce the need for expensive and time-consuming experimental assays, enabling faster and more cost-effective research.
In this project, computational methods (“machine learning” and “artificial intelligence”) will be utilised to identify molecules that can act as both markers of disease and therapeutic agents. Students will utilise data describing potential molecular vectors and cell-expressed targets to form neural networks identifying candidate drug-target combinations.
Benefits
This placement will provide exposure of the students to developed expertise in ML/AI, as applied in a clinical setting. The students will be able to tap directly into that expertise with the opportunity to apply relevant techniques to their own research problem, develop applicable solutions and directly obtain feedback on those solutions. The NMHS will benefit by expanding the network of related specialist knowledge, establishing new collaborative links with the students’ institutions and research groups, participating in unique innovation opportunities, and acquiring knowledge of relevance to work being undertaken on its campuses.
Learn More
https://www.scgh.health.wa.gov.au/
This placement aligns with the work of the Centre for Advanced Technologies in Cancer Research (CATCR), a new research foundation created to advance cancer therapies and their availability (see https://www.catcr.org/).
EMILY MCLEISH
Murdoch University
School of Medical, Molecular and Forensic Science
Skills: leadership; problem solving; data analysis and Machine Learning; R and Python; communication and interpersonal skills and adaptability.
NATALIYA SLATER
Murdoch University
School of Medical, Molecular and Forensic Science
Skills: wide range of molecular and cellular lab techniques; data processing and visualisation using R; critical thinking and effective troubleshooting; working collaboratively; adaptable to changing environments and project requirements.
OncoRes Medical
Project 1: Development of validated testing, training and modelling phantoms / Medical device manufacturing
Project 2: Automation & AI/machine learning
About
OncoRes Medical is a Perth-based medical company dedicated to eliminating the burdens associated with repeat operations following breast-conserving surgery (BCS). The company is developing a hand-held, real-time intraoperative imaging device to improve the detection of residual tumour in the surgical cavity, providing surgeons with the confidence that no residual cancer remains in the breast. This innovative solution is based on technology developed in collaboration with the University of Western Australia and Western Australian Department of Health. OncoRes Medical is based in Nedlands.
OncoRes was founded at the intersection of medicine, science, and humanity with a mission to redefine cancer surgery and eliminate the physical, psychological, and economic burdens associated with repeat operations. Our novel imaging technology - Quantitative Micro Elastography or ‘QME’ - produces real-time diagnostic quality tissue images with best-in-class sensitivity and specificity during oncological surgery.
Our vibrant and energetic team culture promotes curiosity, adventure, courage, resourcefulness and fun. We are committed to doing the best for patients, customers and our company and are constantly looking to the future and finding new ways to make it better. We love working on big challenges and value the contribution of our diverse teammates and collaborators; and are always looking to celebrate our success.
Project
Project 1: Development of validated testing, training and modelling phantoms / Medical device manufacturing
In this project, students will work collaboratively to develop fully validated phantoms and the manufacturing processes to reproduce them. Phantoms will be developed to use across OncoRes Medical’s research, design, development and manufacturing, e.g. device acceptance and QC testing, user training, to assess existing models and validate new models.
As well as the project work, students will participate in their team’s activities, particularly in manufacturing devices and components to full ISO13485 quality.
Project 2: Automation & AI/machine learning
In this project, students will work closely with our software team focusing on automating software infrastructure and tooling used to support all technical teams. This project will focus on automation to get the most out of our software infrastructure tooling.
In addition, working closely with the accessory software and signal processing leads, there is significant opportunity to contribute across our existing machine learning and data pipelines.
Benefits
Learn More
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https://www.oncoresmedical.com/https://www.linkedin.com/company/18733434/
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Instagram: OncoRes_Medical
AYDIN RAEI SADIGH
Edith Cowan University
School of Medical and Health Sciences
Skills: wet lab work (molecular biology, cell culture, flowcytometry, immunoassays etc); clinical study; teamwork and resilience; effective documentation and reporting; laboratory quality control and data analysis.
ABID ALI
Macquarie University
School of Computing
Skills: Natural Language Processing; Machine Learning and Deep Learning; Python programming; text analysis and pre-processing; research and problem solving.
MTPConnect
WA Life Sciences Innovation Hub
Systems and Evaluation: WA Life Sciences Innovation Hub
About
MTPConnect is a federally funded, independent, not-for-profit industry growth centre, working to accelerate the medical technology, pharmaceutical, biotechnology and digital health (MTP) sector in Australia. MTPConnect works at the nexus of all stakeholders involved in the creation and development of novel medical products to support and accelerate their commercialisation pathways. In WA, MTPConnect operates in partnership with the University of Western Australia and the state government to deliver the WA Life Sciences Innovation Hub.
Project
The WA Life Sciences Innovation Hub (WALSIH) is a partnership between MTP Connect, the WA Government and the University of Western Australia (UWA) to accelerate the growth of the state’s MedTech and Pharmaceuticals sector, create new jobs and support economic diversification.
This iPREP Biodesign internship project has three areas of focus:
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Evaluation of priority impact areas for WALSIH including economic, health, social and collaboration domains.
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Establishment of a Innovative Society - Meshpoints “Sub-Constellation” for Healthcare and Life Sciences
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Analysis of Digital Mental Health Application uptake and barriers, including of WA developed tools.
Benefits
Focus 1: Outcomes of the evaluation will be used to promote the WA Health and Life Sciences Innovation sector locally, nationally and internationally and assist with attracting resources and designing and prioritising initiatives to both build on strengths and address gaps.
Focus 2: Health and Life Sciences sector participation in the Innovative Society initiative will provide structure and access to funding to a) support early-stage healthcare innovators and entrepreneurs and b) facilitate collaboration on innovation within and across sectors.
Focus 3: Outcomes of the analysis will inform options for WALSIH to support development and uptake of innovative and effective digital MH tools for the benefit of the WA community.
Learn More
JIE GAO
Western Sydney University
School of Business
Skills: Data analysis (big sample data, regression and model verification, Stata, Python, R and MATLAB, data visualisation); information and data collection, summarizing them in a systematic way; problem solving, embracing challenge, persevering until solutions are found; accounting and finance background; teamwork.
LAURA MARCELA REY GOMEZ
Macquarie University
School of Natural Science
Skills: Search and analysis of scientific literature; data analysis and evaluation; problem solving and creative thinking; verbal communication and public speaking; academic writing and explaining scientific concepts in layman’s terms.
TAYYABA RASHEED AHMED
University of Wollongong
School of Business and Law
Skills: Sustainable banking and ESG implementation; credit and investment analysis; business planning and forecasting; strategic financial management; research oriented business modelling.
ICARO DE OLIVEIRA ROSA
Macquarie University
School of Education
Skills: Work effectively as part of a team; work successfully with limited supervision; cultural competence; quantitative and qualitative research skills; research analysis.
Round 1
Round 1 Projects
VitalTrace
Fetal Monitoring Device
About
VitalTrace is pioneering change in fetal monitoring technology which has been lacking new innovation for over 60 years. Obstetrics is one of the last remaining frontiers of medicine without a basic diagnostic device which presents tremendous opportunities for our company to make change.
VitalTrace is applying cutting edge electrochemical biosensor technology to bring a new standard of care for fetal care during labour.
Project
The VitalTrace team has multiple project opportunities, depending on the skill- set and suitability of the applicants. There are at least three major scopes of work proposed although the project need not be limited to these areas, depending on the team.
We would ideally like to engage a single multidisciplinary team, working to a single goal. These could be:
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Embedded firmware, electronic engineering and software algorithm team - suited for electronic and software engineers/coders with ability to understand clinical context. Working with VitalTrace’s existing project partners and product developers, the team will support the development of a robust, analysis unit, the “back-end” to our current fetal monitoring prototypes.
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New product vertical team - suited for biomedical engineers, individuals with high EQ and/or business and finance background to undertake an end to end initial business case, basic prototyping of second product and market research including qualitative interviews/market research.
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Electrochemistry, R&D and Human trial team - suited for R&D researchers with biochemistry background to conduct basic electrochemistry and biochemistry R&D. Working with VitalTrace to complete the year’s R&D and bench testing goals to optimise the core technology for readiness in testing in a first-in-human trial (potentially world-first data). Optional: experience in human clinical trials.
YASHVI BHATT
University of Western Australia
Centre of Ophthalmology and Visual Science
Skills: Comprehend large amount of information; creating and implementing experimental design; wet lab work (PC2 lab experience, qPCR and protein assays, pharmacological agents preparation., animal work); prepare concise and logically-written material.
MESALIE FELEKE
University of Western Australia
Biomedicine
Skills: Academic and scientific writing; microarray and RNA seq bioinformatic analysis; epidemiological data analysis; cell culture; communication.
Neurotologix
Analysis of dizziness and balance disorders
About
Neurotologix is a WA MedTech company that has built a clinically proven remote patient monitoring system for dizziness and vertigo. The system allows for swifter and more precise diagnoses by specialists. The data collected will facilitate further medical research into understanding the symptoms, causes, and treatment of a range of balance disorders. Neurotologix was the winner of WA Innovator of the Year 2022.
Project
Observing and reviewing the symptoms of balance disorders can be a complex task. Neurotologix has been combining a range of analytical techniques to analyse the data collected to assist the clinician's interpretation.
Working on this project, candidates will have the opportunity to:
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Process video image data in order to help clinical decisions
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Work with eye-tracking data
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Investigate and apply modern time series analysis techniques, including - wavelet transformation and neural networks
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Investigate and apply other machine learning techniques
HANNAH LEEHO
CQUniversity
Health, Medical and Applied Science
Skills: Data analysis (SPSS, R, MATLAB); problem-solving; research and information management; project management; communication.
NAFISEH MIRABDOLHOSSEINI
Western Sydney University
Medicine
Skills: Biomedical device innovation and commercialisation; clinical study, biocompatibility and biosafety; communication, interpersonal skils and teamwork; adaptibility, time management and budget management; QMS and SolidWorks.
North Metropolitan Health Service
Project 1: Clinical Risk Prediction Model for Hospital Acquired Complications (using Machine Learning (ML)
About
The North Metropolitan Health Service (NMHS) serves around 28% of the Western Australia population providing a comprehensive range of adult specialist medical, surgical, mental health and obstetric services, delivered across 5 hospitals. This includes Osborne Park, King Edward Memorial and Graylands hospitals.
NMHS employs 12,805 people dedicated to delivering sustainable, quality health services to our patients, promoting and improving health outcomes in our community, and taking care of each other. The NMHS Innovation and Development department provides support for creative ideas that will positively impact organisational workflow, communications and patient care.
The NMHS focus is to lay the foundations for future success through connecting services across the hospitals and engaging the workforce and the community. Together with the NMHS partners this will create quality connections and greater accountability and foster an environment ready for change and innovation.
https://www.nmhs.health.wa.gov.au/
An automated and self-trained ML model that analyse & learn to identify the risk factors and calculate that risk & probability of a patient developing certain medical conditions or infections i.e. urinary tract infections, bloodstream infections, mortality probability etc. The model has to be customisable to perform risk calculations for multiple defined problem domains.
This project involves:
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Linking patient demographics and clinical data.
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Shortlisting of clinically significant variables.
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Self-training Machine Learning (ML) model for most of the HACs.
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Training the customisable model to be fully automated.
The proposed solution could be in the form of a HAC Risk calculator app that would be used by clinical staff in the wards to calculate real-time risk of HACs.
This will be first of its kind application of Machine Learning in WA health system to predict risk of undesirable patient outcome and prompt timely intervention to prevent it. To-date, no such tools or prediction models have been developed specific to WA patient casemix. Once tested in NMHS setting, the model can be rolled out to state-wide health system, possibly accounting for diverse patient profiles across rural vs metropolitan public hospitals.
BENJAMIN MCFADDEN
University of Western Australia
Computer Science and Software Engineering
Skills: Software development and engineering; machine learning; Python programming; data analysis for health data; written and interpersonal communication.
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QIU YUE ZHANG (VIKI)
Macquarie University
Economics
Skills: Large panel dataset and time series regression and modelling; data analysis (Python, R, Stata, MATLAB); academic writing; literature review; critical thinking; project design and management.
Md TAUHIDUL ISLAM
Murdoch University
Public Health
Skills: Public health program design, development and implementation; quantitative analysis; research and technical writing; statistical software; systematic and scoping review.
EHSAN ALVANDI
Western Sydney University
Medicine
Skills: Commercial acumen; teamwork; time management; leadership; database management.
Project
North Metropolitan Health Service
Project 2: Improving public access to clinical research trials within WA using artificial intelligence (AI)
Department of Education
Project
An automated and self-trained NLP model that can decode medicalised research information into summarised and simplified information about clinical research projects.
This project aims to develop a search tool/engine which will facilitate effective searching of research proposals, including filtering by eligibility criteria and disease information, with an interface that supports positive user experience (UX) for the WA community.
Working on this project students will:
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Determine the best means to address the issue of inaccessible medical terminology, applying AI, ML and NLP model to address language limitations.
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Design and develop search engine/tool, defining search tool requirements and functions.
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Engaging with a user group, design an interface for a positive user experience (UX).
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Engage with key stakeholders to develop communication plan a to promote a completed tool to public.
RICHARD ADJEI DWUMFOUR
Curtin University
Accounting, Economics and Finance
Skills: Data science; multivariate regression and time series analysis; STATA, R and Python; team player; eclectic.
KAIXIANG ZHU
CQUniversity
Engineering and Technology
Skills: Machine learning; software development; web development; software project design and management; clinical medicine background.
Development of a staff mental health self-care tool
About
The Department of Education aims to deliver a high quality education to all students in all learning environments. We are committed to all students achieving their best and being lifelong learners who contribute actively to their communities and to society.
We work with parents, families, agencies and organisations to prepare students with the skills, understandings and values to achieve their best and make a positive contribution to society.
Project
The Department of Education Western Australia (the Department) is seeking to develop a mental health self-care tool that will be accessible to all staff.
The Department has undertaken consultation with all staff cohorts over a number of years to gather information about staff health and wellbeing and this data will assist in the development of the tool.
The tool(s) will be accessible to all staff including those who work in the most remote areas of Western Australia and be tailored to staff across employment type, career and life stages.
STELLA RODGERS
University of Western Australia
Education
Skills: Communication (written and oral presentation); training; adaptability; interpersonal; leadership and teamwork.
LEILA MOKHTARI
University of Wollongong
Education
Skills: Data collection and analysis; searching for information; computer skills (databases, technical support); planning and scheduling; teamwork.
ZHILI YANG
Western Sydney University
Business
Skills: Research design and data analysis; written and verbal communication; cross-cultural competence; employee relations; time management.
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NGOC DANG KHOA NGUYEN
Central Queensland University
Business
Skills: Research writing; data analytics; team management; negotiations; problem-solving.
Vision Pharma
(PYC Therapeutics/Lions Eye Institute)
Direct differentiation of neurons from induced pluripotent stem cells; characterization and analysis.
About
Vision Pharma Pty Ltd was named the WA Innovator of the Year 2021 for developing the world's first precision medicine to treat the blinding eye disease Retinitis Pigmentosa type 11.
Vision Pharma is a joint venture between the PYC Therapeutics and Lions Eye Institute. The company’s VP-001 medicine is intended to correct the impact of a genetic mutation which causes Retinitis Pigmentosa type 11, an eye disease which causes blindness. It is the most common form of inherited retinal disease, with about one in every 3000 to 4000 people globally impacted, usually culminating in blindness before 50 years of age.
Vision Pharma is offering a new generation of RNA therapeutics which are supported by their revolutionary delivery technology based on Cell Penetrating Peptides (CPPs) to overcome the ‘delivery challenge’ in genomic therapies. Differentiated drug delivery capability and RNA drug design expertise mean they have the skills and capability to discover and develop RNA-targeted therapeutics in a truly innovative way. With three defined preclinical programs for Inherited Retinal Diseases, and a strong focus on Central Nervous System diseases, guided by world-class scientists and business leaders, they are at the forefront of innovation in the biotechnology sector.
Find out more:
Project
The candidate will utilise their research knowledge and technical skills to develop and optimise a protocol/s to differentiate neuronal cell types from induced pluripotent stems cells (iPSC) derived from a healthy subject and a subject with a neurological disorder.
Activities include:
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Quality Control assessments
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Investigating the expression of markers of neuronal differentiation using molecular techniques, and immunocytochemistry and microscopy
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Stem cell culture and imaging
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Cellular harvest and processing
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Designing and run flow cytometric assays
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Data analysis and interpretation
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Experimental documentation
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Present data and communicate outcomes of the project
This work will further company's technical capability in central nervous system (CNS) disease; add to the company’s fundamental knowledge of the physiological effects of inherited neurological disease; and strengthen the predictive power of in vitro pharmacological assays.
LEON LARCHER
Murdoch University
Centre for Molecular Medicine and Innovative Therapeutics
Skills: Data analysis and interpretation; wet lab skills (i.e. molecular biology, cell culture); time and project management; resilience and determination; teamwork and communication.