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Spatial & Single-Cell Computational Immunogenomics for Cancer Diagnosis

University of Adelaide
Adelaide (Suburb), Metropolitan Adelaide (AU)
$75,888 to $102,040 per annum plus an employer contribution of 17% superannuation applies.
Closing date
18 Jul 2024

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Health Science
Job Type
Faculty Member
Employment - Hours
Full time
Fixed term


(Level A) $75,888 to $102,040 per annum plus an employer contribution of 17% superannuation applies.

Fixed term, full time position available for 24 months.

Advance cancer diagnosis by analysing immune system responses and treatment efficacy using spatial and single-cell computational immunogenomics.

The position is for a postdoctoral fellow in spatial and single-cell computational immunogenomics for cancer diagnosis. This position will advance cancer diagnosis by analysing immune responses and treatment efficacy through data-driven research and a multi-omic approach. Exploring the dynamics of circulating immune cells in blood reveals crucial insights into the immune system's response, its efficacy against metastatic cancer, and its reaction to treatments. Profiling peripheral blood immune single cells and circulating cytokines, we uncovered patterns of immune cell communication and composition linked to metastatic progression (Mangiola et al. 2024). 

This exciting position aims to expand this research to study the local tumour microenvironment and apply this approach to identify individual immune characteristics influencing immunotherapy success. We aim to employ a multiomic approach, analysing extensive patient data across all stages of disease progression. This research will utilise state-of-the-art facilities, including 10x Xenium, 10x CITE-seq, Milliplex and proteomics.  We are searching for a dynamic individual for the Computational Biologist/Bioinformatician/Biostatistician role. Managing personal research funds is a possibility depending on the appointment level and the candidate's experience.

Key responsibilities: Develop and apply advanced AI large-language models to analyse large-scale single-cell datasets; Contribute to the expansion and refinement of our large-scale single-cell database; and collaborate with a multidisciplinary team to advance the field of precision oncology.

To be successful you will need: 

Explicitly address each selection criteria

  • PhD in Computational Biology, Bioinformatics, Computer Science, or a closely related field with a strong focus on machine learning and deep learning applications.
  • Demonstrable experience in analysing large-scale single-cell genomic data.
  • Proficiency in programming languages commonly used in computational biology and data science, such as Python and R, with the ability to handle complex data analysis tasks. Please provide publicly available examples.
  • A strong record of research, evidenced by publications in peer-reviewed journals or presentations at significant conferences, particularly in areas related to AI, language modelling, computational biology, bioinformatics, or immunogenomics.

Enjoy an outstanding career environment

The University of Adelaide is a uniquely rewarding workplace. The size, breadth and quality of our education and research programs - including significant industry, government and community collaborations - offers you a vast scope and opportunity for a long, fulfilling career.

It also enables us to attract high-calibre people in all facets of our operations, ensuring you will be surrounded by talented colleagues, many world-leading. Our work's cutting-edge nature - not just in your own area, but across virtually the full spectrum of human endeavour - provides a constant source of inspiration.

Our culture is one that welcomes all and embraces diversity consistent with our Staff Values and Behaviour Framework and our Values of integrity, respect, collegiality, excellence and discovery. We firmly believe that our people are our most valuable asset, so we work to grow and diversify the skills, knowledge and capability of all our staff.

We embrace flexibility as a key principle to allow our people to manage the changing demands of work, personal and family life.

In addition, we offer a wide range of attractive staff benefits. These include: salary packaging; flexible work arrangements; high-quality professional development programs and activities; and an on-campus health clinic, gym and other fitness facilities.

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Your faculty's broader role

The Faculty of Health and Medical Sciences contains one of Australia's largest concentrations of leading health researchers, teachers and clinical titleholders. It's comprised of eight schools and a number of specialist disciplines, institutes and centres, variously focused on world-class research, and training the next generation of: medical doctors; surgeons; dentists; nurses; psychiatrists; psychologists; and other health professionals.

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If you have the talent, we'll give you the opportunity. Together, let's make history.

Click on the link below to be taken through to the online application form.

Please ensure you submit a cover letter, resume, and upload a document that includes your responses to all of the selection criteria for the position as contained in the position description or selection criteria document.

Applications close 11:55pm, 18 July 2024.

The University reserves the right to close this advertisement before the closing date if a suitable candidate is identified.

For further information

For a confidential discussion regarding this position, contact:

Stefano Mangiola
Group Leader, SAiGENCI

You'll find a full position description and/or selection criteria below: (If no links appear, try viewing on another device)

The University of Adelaide is an Equal Employment Opportunity employer committed to providing a working environment that embraces and values diversity and inclusion. Female applicants, people with a disability and/or and Aboriginal and Torres Strait Islander people who meet the requirements of this position are strongly encouraged to apply. If you have any support or access requirements, we encourage you to advise us at time of application. 

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