Doktorarbeit an der University of Western Australia

Please apply through for a Higher Degree by Research (HDR) scholarship on the UWA website. www.uwa.edu.au/study/fees-and-scholarships/hdr-scholarships 

Other international scholarships matching the HDR one could be considered.

Artificial reefs are increasingly being deployed along coastlines worldwide for a range of purposes, including recreation, habitat enhancement and coastal management. While numerical and physical modelling are commonly used to inform reef design and approvals, there remains limited quantitative, field‑based evidence evaluating how artificial reefs interact with nearshore hydrodynamics, sediment transport and beach evolution once constructed, particularly in high‑energy wave environments.

A central motivation for this project is the need to empirically assess post‑construction coastal response to artificial reefs, and to evaluate assumptions commonly made during the design and approval process. By resolving coastal processes across a range of temporal and spatial scales, the project will improve understanding of how reef geometry, placement and wave climate influence coastal behaviour.

This project will investigate the coastal impacts of artificial reefs, with a focus on understanding how engineered reef structures modify wave transformation, nearshore circulation, sediment transport pathways and shoreline response. The research will address key knowledge gaps related to whether, and under what conditions, artificial reefs produce measurable changes to beach morphology, erosion and accretion patterns, or nearshore sediment dynamics.

The project will employ a combination of field‑based observations (e.g. wave and current measurements, beach and seabed surveys, sediment monitoring) and remote‑sensing and data‑driven analyses (e.g. satellite imagery, UAV surveys, coastal monitoring datasets). Outcomes will provide robust, evidence‑based insights to inform the design, monitoring and management of artificial reefs in energetic coastal environments. 

Read more about the project here.

Applicants will be required to apply for available scholarship opportunities. 

Any fully-funded scholarship opportunities will be linked to this project opporutnity via HDRhub. 

Dr Jonathan Chee [email protected], Institute for Respiratory Health

Kofi Stevens [email protected], Institute for Respiratory Health  

Background  

Mesothelioma is a rare and aggressive cancer with limited treatment options and poor survival outcomes. Although treatments designed to activate the immune system against cancer have demonstrated some clinical benefit, the majority of mesothelioma patients fail to respond. 

Emerging evidence implicates copper as a critical factor in tumour progression. Copper accumulates in mesothelioma tissue, where it promotes tumour growth, immune evasion, and resistance to chemotherapy. Drugs that bind and reduce copper levels (copper chelators) are already approved for non-cancer indications, offering a unique opportunity for drug repurposing. 

This project will explore how manipulating copper availability affects tumour cell behaviour, immune cell function, and overall treatment response. Our goal is to determine whether copper chelation can improve the efficacy of standard therapies and immune-based treatments in mesothelioma. 

Aims 

• Investigate copper levels alters tumour cell behaviour and gene expression, including chemotherapy transporters, MHC-I, and PD-L1.
• Examine how copper affects tumour cell sensitivity to chemotherapy.
• Assess the impact of copper on immune cell function and tumour visibility using in vitro T cell–tumour cell killing assays. 
• Characterise how copper chelation therapy modulates immune cell composition and activity within the tumour microenvironment. 
• Evaluate the in vivo effectiveness of copper chelation therapy, alone or in combination with chemotherapy and/or immunotherapy, and its impact on the tumour microenvironment. 
• Use CRISPR-Cas9 to knock out key copper transporter genes in tumour and immune cells to dissect their role in treatment response. 
• Analyse publicly available datasets to investigate expression of copper-regulatory genes in cancer patients and correlate these with clinical outcomes and treatment responses. 

Outcomes 

Chance to travel to Sydney to work with UNSW collaborators. 

Read more about the project here.

Multiple funding sources from Cancer Council WA, WA Department of Health.

Dr Jonathan Chee [email protected], Institute for Respiratory Health

Dr Nicola Principe [email protected], Institute for Respiratory Health

Project Title 

Immunotherapy, particularly immune checkpoint blockade (ICB), has transformed the treatment of advanced lung cancer and mesothelioma. However, up to 70% of patients do not respond to these therapies, highlighting an urgent need to improve their effectiveness. 

One of the major barriers to successful immunotherapy is the presence of regulatory T cells (Tregs) in the tumour. These cells suppress the immune system and prevent it from attacking the cancer. Recent research suggests that Tregs inside tumours rely heavily on cholesterol and lipid metabolism to maintain their function. Interestingly, clinical studies have shown that patients taking cholesterol-lowering drugs may respond better to ICB, suggesting a potential way to target Tregs and improve outcomes. 

Project Overview 

This project aims to understand how altering lipid metabolism, particularly cholesterol, can reduce Treg-mediated immune suppression and enhance the body’s immune response to cancer. 

Aims  

• Investigate how cholesterol-lowering drugs affect Treg survival, function, and gene expression. 
• Assess how changes in lipid metabolism alter Treg suppression of anti-tumour T cells. 
• Use co-culture assays to test how modifying Treg metabolism impacts immune cell killing of cancer cells. 
• Apply CRISPR-Cas9 to disrupt key metabolic genes in Tregs and explore effects on immune suppression. 
• Evaluate how cholesterol-lowering treatments such as statins influence Treg populations in the tumour microenvironment. 
• Test whether combining metabolic therapies with ICB improves tumour control in mouse models of lung cancer and mesothelioma. 
• Analyse patient data to explore links between cholesterol metabolism genes, Treg signatures, and immunotherapy outcomes. 

Why Join This Project? 

• Work at the intersection of immunology, metabolism, and cancer therapy.
• Gain experience in cutting-edge techniques including CRISPR, flow cytometry, and in vivo tumour models, lipidomics and genomics.
• Contribute to translational research with real clinical relevance.
• Opportunity to collaborate with national experts in tumour immunology and lipid metabolism.

Read more about the project here.

Multiple funding sources from Cancer Council WA, WA Department of Health.

Read more about the project here.

A successful PhD candidate in this project requires strong skills in experimental design, molecular biology, and ecological genomics to conduct and analyze evolution experiments with coral-algal symbioses.

Additionally, proficiency in field-work, statistical modelling, bioinformatics, and data visualization is essential to interpret complex physiological and evolutionary data in the context of climate change.

Experience in laboratory techniques for culturing algae or cells is preferred, as this project involves maintaining and experimentally evolving Symbiodiniaceae strains. Hands-on expertise in algal or cell culture methods will be ideal for conducting controlled experiments and ensuring the consistency of symbiont populations across various environmental conditions.

Potential candidates should undertake the following:

• International & Australian candidates confirm fulfilment of all admission requirements at UWA PhD Program.
• Send a CV & cover letter, briefly outline research interests.

Professor Andreas Wicenec | [email protected]; Director, Data Intensive Astronomy

Dr. Fuling Chen | [email protected]; Research Fellow, Data Intensive Astronomy

Machine learning models, including linear regression, ensemble methods like random forests, and deep neural networks, have transformed medical research by enabling breakthroughs in diagnostics, drug discovery, and personalized treatment. However, these models often function as "black boxes," offering little insight into how they arrive at predictions. This lack of interpretability hinders trust and adoption in healthcare, where understanding the reasoning behind decisions is critical for clinical validation and patient safety.

This PhD project aims to address the urgent need for explainable AI (XAI) in medical research by developing algorithms that combine predictive accuracy with clear, interpretable outputs. Emerging approaches like Kolmogorov-Arnold Networks (KANs) and techniques such as SHAP or LIME provide pathways to make AI decisions transparent. By creating models that explain their processes and results, this research will empower medical professionals to validate AI outputs, uncover biological insights, and ensure ethical, equitable healthcare solutions.

As a PhD candidate, you will design and implement novel XAI models tailored for medical datasets, including epidemiology, genomics, and epigenetics data. Using Python and frameworks like PyTorch or scikit-learn, you will prototype algorithms, test them on real-world medical benchmarks, and evaluate both accuracy and interpretability. You will collaborate with AI experts and clinicians, contributing to publications in top journals and conferences.

Your work will advance the field of medical AI by creating trustworthy, interpretable models that could improve disease detection or treatment planning. We welcome candidates with a background in computer science or related fields, proficiency in programming, and a passion for impactful research.

Read more about the project here.