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Field
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RNA-seq, single-cell ATAC-seq, multiome, etc). Demonstrated ability to effectively communicate about complex bioinformatics problems to both technical and non-technical audiences. Independent, highly
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works to interpret genomes and distill the immensely complex networks that form the foundation of human biology and disease, through accurate machine learning models. Current areas of interest include
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related disorders (ADRD). The Lab’s overarching goals are 1) to achieve a better understanding of the complex causes and mechanisms leading to ADRD, 2) to improve early detection and longitudinal monitoring
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following areas: human neuroimaging analysis (e.g., FSL, FreeSurfer, SPM12, ANTS, etc.), complex network analysis (e.g., modularity, centrality, etc.), and multi-omics data analysis. Strong programming skills
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psychological assessments. Training in professional skills development will also be offered, including guidance in writing grants and papers, assistance in building a professional network, supervising trainees
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stronger, more equitable health systems across Australia. We work closely with government and industry partners to solve complex challenges, inform better policy, and deliver evidence that makes a difference
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disease treatment through advanced Digital Twin technology. Based in the Department of Computing and Mathematics, you will lead the design and development of AI-driven models applied to complex healthcare
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experienced in meaningful community engagement, with a genuine interest in addressing problematic narratives for Aboriginal peoples. Your critical thinking skills help you navigate complex issues with ease
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and Autonomous Maritime Navigation, partially funded within, Operational Zero Emission Ferries – Safe and Efficient Human-Autonomy Teaming in Complex Maritime Transport Systems, (BZERO) The position
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technical oversight of the ToF-SIMS facility Foster a collaborative, inclusive, and productive research culture Represent the JdLC in national and international networks Research Develop an internationally