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on the application of advanced or specialist or technical research skills or processes, including computer vision, machine learning and data management. Assists in the conduct of complex tasks involving all stages
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Experience in Machine Learning OR human factors, HCI or psychology will be highly regarded. Based at our picturesque and Vibrant St Lucia Campus About UQ As part of the UQ community, you’ll have the
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School of Mathematics and Physics Analytics for the Australian Grains Industry (AAGI) Play a lead role in developing crop trait prediction solutions Utilizes physics-informed machine learning (PIML
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), and the ability to learn new procedures. High levels of computer proficiency with experience using MS Word, MS Excel, PowerPoint and EndNote. Dedication to subject confidentiality and research ethics
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models. In-depth understanding of linear algebra and fundamentals of deep learning. Knowledge of Transferability in Machine Learning is desirable. Strong background in multimedia and computer vision tasks
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machine learning methods to predict protein structures, predict peptide and protein interactions, and design new peptide drugs and crop protection agents. The work is funded by the Australian Research
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, co-design workshops, cluster randomized controlled trials (RCTs), implementation science, data linkage, data science, machine learning and artificial intelligence. These are research focused positions
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bioinformatician/data scientist to use modelling and machine-learning approaches to learn from large data sets to inform further strain engineering or bioprocess optimisation rounds. Whilst the role is academic in
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) to use computational analysis and machine learning methods to interpret data relating to the screening and development of peptide-based drug leads with a particular focus on optimising their permeability
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combination of relevant experience and/or education/training . Practical experience with molecular biology, ELISA assays, flow cytometry. High-level computer and database literacy skills, including