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for research leadership. Conceptualisation and completion of data analyses with skills related to epidemiology, biostatistics and modelling including machine learning methods A sound understanding of clinical
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machine learning, multi-level complex data engineering, emerging technologies in transport and economics analysis. We’re offering this role as a hybrid position as part of QUT’s commitment to embracing
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modelling, discrete choice modelling, designing choice experiments and machine-learning methods to address sustainable transport and mobility challenges. We’re offering this role as a hybrid position as part
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demonstrated aptitude to engage collaboratively with industry partners and other external stakeholders. Knowledge of optimisation solvers and proficiency in machine learning algorithms and their practical
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highly computer literate, with experience in Microsoft Office and university software, and the willingness to learn new technologies. Experience in electrical engineering, microwave frequency technology
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Schools teach an array of programs and degrees carefully structured to meet the demands of future industry. The University is ranked in the top 2% of universities worldwide, with over 85% of its assessed
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Schools teach an array of programs and degrees carefully structured to meet the demands of future industry. The University is ranked in the top 2% of universities worldwide, with over 85% of its assessed
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with single-cell omics (Level A). This research aims to develop new statistical and machine learning methods to integrate and analyse data from genome-wide association studies (GWAS) and single-cell
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biobank featuring thousands of novel microorganisms from the human gut, and machine learning models to predict how entire microbial communities will respond to changes in their environment. The successful
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You Completion (level A and B) or near completion (level A) of a PhD in the field of Information Retrieval, Natural Language Processing, or Machine Learning on Textual Data. Demonstrated expert