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Field
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analysis of single-cell and spatial transcriptomics data, correlating findings with imaging data Present findings at lab meetings and international conferences Contribute to manuscript preparation and grant
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of muscle hypertrophic growth; 2) identifying the glucose transporter(s) activated by resistance training in muscle; and 3) examining the connections between glucometabolic flux and the muscle transcriptome
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, and information hub for rare pediatric and adult cancers, and develop foundational methods and resources for the integration of single-cell and clinical transcriptomes. Responsibilities* Process raw
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genomics data sets on the genome, epigenome, and transcriptome in disease-relevant tissues/cells and use of computational approaches to integrate and analyze this data to identify the molecular components
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of high-throughput imaging and molecular data (i.e., genome, transcriptome, epigenome, and more). The methods would be able to systematically integrate biomedical/biological knowledge to improve
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Environment OBI Scholars will also have access to: Advanced imaging and data analysis resources, including two-photon and light-sheet microscopy, STED, spatial transcriptomics (Xenium and Merscope), cryo-EM
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with CRISPR technologies, transcriptomics, imaging or zebrafish models is a bonus, as is familiarity with GitHub, Jupyter or R Markdown for reproducible analysis. Most importantly, you're collaborative
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quantitative readouts using methods such as transcriptomics, high-content imaging, flow cytometry, proteomics, single-cell analysis, drug response or other molecular/cellular phenotypes. Collaborate across UNSW
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TO HIRE A PROFESSIONAL WITH THE FOLLOWING PROFILE: - Degree in Biology, Biochemistry, or Biomedicine. Reference: 2026/185 Project: PI25/02069 High-content Screening (HCS) and transcriptomics
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of muscle hypertrophic growth; 2) identifying the glucose transporter(s) activated by resistance training in muscle; and 3) examining the connections between glucometabolic flux and the muscle transcriptome