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(PhD entry Level - $108,156 p.a.) Join a collaborative and cutting-edge research environment working with world-class researchers. Apply statistics, bioinformatics, and machine learning methods
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members Commitment to the principles of equity, diversity and inclusion. Desirable characteristics: Understanding of bioinformatics. Experience with HPAEC-PAD and HPLC systems. The path to Adelaide
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. Using bioinformatics, data science, or behavioural science – including artificial intelligence, you will drive innovative solutions to data challenges, support impactful research and help translate
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modelling of neural systems Bioinformatics Imaging genetics Neuroimaging techniques (MRI, MEG, EEG) Comparative or cross-species neuroscience Excellent problem-solving, organisational, and communication
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activities, focusing on bioinformatics analysis of metabolomics and lipidomics data, metabolic flux analysis, and integration of multi-omics datasets. You will also assist in developing bioinformatic tools and
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for the relevant discipline area (e.g., AI/Machine Learning, Bioinformatics). A proven track record of research and scholarly achievements in AI/Machine Learning, and ideally with some exposure to applications in
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Computer Science, Computational Chemistry, bioinformatics) and have extensive experience in academia or industry with a focus in computational drug discovery. Prior experience working with GPCRs would be
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, and business, and is at the forefront of computing research in Australia and internationally with close links to major computing research initiatives, including Melbourne Bioinformatics, CSL
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publications and presentations. Demonstrate expertise in soil microbiomes, metagenomics, and plant-soil microbiome interactions. Have experience with soil incubations, bioinformatics, and statistical modelling
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publications and presentations. Demonstrate expertise in soil microbiomes, metagenomics, and plant-soil microbiome interactions. Have experience with soil incubations, bioinformatics, and statistical modelling