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prediction models in Neurology using EEG data via Deep Learning (DL) techniques. In this prospective and longitudinal study, the outcome of interest is cognition over time. This position will be under
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language models (LLMs), including tasks such as data preprocessing, feature extraction, model training, and evaluation. Background in Generative AI research, including multi-modal LLMs. Background in AI
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to gender—and demonstrated expertise in advanced statistical methods (e.g., multilevel modelling). The successful candidate will work closely with the Principal Investigator, Dr. Verena Klein, a PhD student
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of clinical decision support systems and multimodal analytic platforms to translate advanced data science solutions into critical care. The main focus of this position is on the analysis of the signals
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PhD Research Fellow in Chemistry-focus on Experiments in Chemical Kinetics and Heterogeneous Catalys
Apply for this job See advertisement About the position Position as PhD Research Fellow in Chemistry with focus on Experiments in Chemical Kinetics and Heterogeneous Catalysis is available at the Centre
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written and verbal communication skills, experience with developing and implementing Bayesian statistical models, and be proficient in computer programming in e.g. R or Python, and C/C++. Please ensure you
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(Academic Level A) Visa sponsorship may be available for this position Based at our St Lucia Campus - Brisbane About This Opportunity If you are passionate about computational modelling, thrive on solving
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Justin Sheffield. This project aims to transform our understanding of soil moisture (SM) variability and its interactions with land-atmosphere processes. The project will use cutting-edge modelling, data
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UKESM1 or similar models, advanced data analysis and machine learning, would be advantageous. Grade E: You will be near completion of a relevant PhD or have equivalent research experience, and be able
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Justin Sheffield. This project aims to transform our understanding of soil moisture (SM) variability and its interactions with land-atmosphere processes. The project will use cutting-edge modelling, data