About QIMR Berghofer:
QIMR Berghofer is a world-leading translational medical research institute focused on improving health by developing new diagnostics, better treatments and prevention strategies, specifically in the areas of Cancer, Infection and Inflammation, Mental Health and Neuroscience, and Population Health. Based in Herston, Brisbane and working in close collaboration with clinicians and other research institutes, QIMR Berghofer is home to more than 600 scientists, students and non-research staff.
About The Genomics and Machine Learning Lab (GML) Laboratory:
The Genomics and Machine Learning Lab (GML) studies cancer and infected tissues in patient samples and mouse models. They generate novel data from spatial and single cell technologies and develop new computational and statistical methods to find clinically important patterns from this complex data. They pioneered the merging of two big data fields, sequencing, and imaging, to advance understanding of pathological processes one cell at a time and across all cells within a diseased tissue. By mapping cell types, their spatial organisation and cell-cell interactions in tissues, GML focuses on discovering new patterns and cellular regulation mechanisms that are hidden from traditional research approaches. Examples of outcomes include cell and gene markers for predicting cancer progression risks, stratifying disease subtypes, discovering new drug targets to modulate the immune systems, and adding new capabilities for prioritising drugs most effective to each patient.
The National Centre for Spatial Tissue AI Research (NCSTAR) at QIMRB will serve as a centre of excellence for accelerating scientific and clinical progress in spatial biology. As a collaborative hub for integration of cutting-edge deep learning AI models with state-of-the-art spatial biology research, the NCSTAR will train the next generation of spatial biology researchers, and drive new discoveries to enable the translation of research into clinical applications. NCSTAR staff will work collaboratively across QIMRB and multi-institute partnerships and work closely with QIMRB Scientific Services.
Role Purpose / Responsibilities:
Key Responsibilities include:
* Innovate and implement advanced deep learning approaches for robust feature extraction and prediction models using spatial omics, focusing on algorithms that integrate spatial sequencing with histopathological images for diagnostic and prognostic methods.
* Stay at the forefront of rapidly evolving technologies and scientific knowledge in machine learning, spatial omics, and computational biology, tackling complex datasets and computational challenges with innovative problem-solving skills and robust analytical capabilities.
* Utilise high-performance computing systems and cloud computing environments for large-scale data processing and analysis, ensuring cross-disciplinary collaboration with scientists, clinicians, and technologists while promoting excellence and integrity, adhering to the highest quality and ethical standards.
About You:
* PhD (or near completion) in Computational Biology, Bioinformatics, Computer Science, or a related field, with a significant focus on machine learning and deep learning.
* Proficiency in developing and implementing advanced machine learning techniques, including deep learning frameworks such as TensorFlow or PyTorch.
* Experience in applying/developing computational and bioinformatic methods to cancer research, particularly in analysing spatial omics data.
* Strong background in using high-performance computing systems, GPU applications, and cloud computing environments for large-scale data processing and analysis.
* Capacity to innovate and develop new methodologies for integrating various data types.
* Robust publication history in peer-reviewed journals, reflecting deep learning, spatial omics, or related fields.
Please refer to the Position Description for a more detailed description of the role, responsibilities and selection criteria.
Remuneration: Salary range is $92,403 to $99,142 p.a. plus super and salary packaging. This is a full-time, fixed-term appointment for 3 years.
For further information: Please contact Quan Nguyen via email [email protected]
Closing Date: 20 August 2024
To submit an application, it must be via the QIMR Career Page https://www.qimrberghofer.edu.au/careers/
All applicants must supply the following documents: Resume and Cover letter addressing the selection criteria outlined in the Position Description.
What we offer:
* Salary Packaging
* State of the art facilities
* Stimulating work setting focussed on cutting edge medical research
* Supportive/collaborative team environment
* Parental Leave Provisions
QIMR Berghofer is a world-leading translational medical research institute focused on improving health by developing new diagnostics, better treatments and prevention strategies, specifically in the areas of Cancer, Infection and Inflammation, Mental Health and Neuroscience, and Population Health. Based in Herston, Brisbane and working in close collaboration with clinicians and other research institutes, QIMR Berghofer is home to more than 600 scientists, students and non-research staff.
About The Genomics and Machine Learning Lab (GML) Laboratory:
The Genomics and Machine Learning Lab (GML) studies cancer and infected tissues in patient samples and mouse models. They generate novel data from spatial and single cell technologies and develop new computational and statistical methods to find clinically important patterns from this complex data. They pioneered the merging of two big data fields, sequencing, and imaging, to advance understanding of pathological processes one cell at a time and across all cells within a diseased tissue. By mapping cell types, their spatial organisation and cell-cell interactions in tissues, GML focuses on discovering new patterns and cellular regulation mechanisms that are hidden from traditional research approaches. Examples of outcomes include cell and gene markers for predicting cancer progression risks, stratifying disease subtypes, discovering new drug targets to modulate the immune systems, and adding new capabilities for prioritising drugs most effective to each patient.
The National Centre for Spatial Tissue AI Research (NCSTAR) at QIMRB will serve as a centre of excellence for accelerating scientific and clinical progress in spatial biology. As a collaborative hub for integration of cutting-edge deep learning AI models with state-of-the-art spatial biology research, the NCSTAR will train the next generation of spatial biology researchers, and drive new discoveries to enable the translation of research into clinical applications. NCSTAR staff will work collaboratively across QIMRB and multi-institute partnerships and work closely with QIMRB Scientific Services.
Role Purpose / Responsibilities:
Key Responsibilities include:
* Innovate and implement advanced deep learning approaches for robust feature extraction and prediction models using spatial omics, focusing on algorithms that integrate spatial sequencing with histopathological images for diagnostic and prognostic methods.
* Stay at the forefront of rapidly evolving technologies and scientific knowledge in machine learning, spatial omics, and computational biology, tackling complex datasets and computational challenges with innovative problem-solving skills and robust analytical capabilities.
* Utilise high-performance computing systems and cloud computing environments for large-scale data processing and analysis, ensuring cross-disciplinary collaboration with scientists, clinicians, and technologists while promoting excellence and integrity, adhering to the highest quality and ethical standards.
About You:
* PhD (or near completion) in Computational Biology, Bioinformatics, Computer Science, or a related field, with a significant focus on machine learning and deep learning.
* Proficiency in developing and implementing advanced machine learning techniques, including deep learning frameworks such as TensorFlow or PyTorch.
* Experience in applying/developing computational and bioinformatic methods to cancer research, particularly in analysing spatial omics data.
* Strong background in using high-performance computing systems, GPU applications, and cloud computing environments for large-scale data processing and analysis.
* Capacity to innovate and develop new methodologies for integrating various data types.
* Robust publication history in peer-reviewed journals, reflecting deep learning, spatial omics, or related fields.
Please refer to the Position Description for a more detailed description of the role, responsibilities and selection criteria.
Remuneration: Salary range is $92,403 to $99,142 p.a. plus super and salary packaging. This is a full-time, fixed-term appointment for 3 years.
For further information: Please contact Quan Nguyen via email [email protected]
Closing Date: 20 August 2024
To submit an application, it must be via the QIMR Career Page https://www.qimrberghofer.edu.au/careers/
All applicants must supply the following documents: Resume and Cover letter addressing the selection criteria outlined in the Position Description.
What we offer:
* Salary Packaging
* State of the art facilities
* Stimulating work setting focussed on cutting edge medical research
* Supportive/collaborative team environment
* Parental Leave Provisions
