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- focusing on foundational logic and systems, strategic implementation and emerging technology. This is a full-time, non-tenure track position. Key Responsibilities: Teaching Teach four courses per semester
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numerical models and machine learning tools to predict loads, assess structural responses, and identify damage under extreme conditions. By combining computational simulations with data-driven approaches
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Understanding how low UPF1 expression leads to drug resistance in bladder cancers School of Medicine and Population Health PhD Research Project Self Funded Dr Ruth Thompson, Prof Syed Hussain
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research profile to further integrating wet-lab techniques (such as single-cell sequencing, -omics) with advanced data analysis, for example through bioinformatics, machine learning, or AI. Themes such as
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, G. et al. Machine learning and wearable sensors for automated Parkinson’s disease diagnosis aid: a systematic review. J Neurol 271, 6452–6470 (2024). https://doi.org/10.1007/s00415-024-12611-x Nayan
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About the Opportunity The Lecturer will teach introductory courses in architectural drawing, sketching, studio design, computer modeling, architectural history, technology, or project case studies
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data. Develop and apply machine learning models to estimate uncertainty in climate impact statements. Analyse spatial and temporal patterns and trends in climate-extreme impacts. Cross-validate
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motivated to acquire new skills. Candidates must be fluent in English and/or French with scientific writing skills. The doctoral contract will take place at the CRISMAT laboratory (https://crismat.cnrs.fr
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Babinski, PhD. This position will report to Research Professor Leslie Babinski. CIDR is a school-based research and professional learning initiative designed to strengthen adolescent wellbeing and literacy
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different environments influence behaviour and wellbeing. Advanced analytics, including AI and machine learning, will be used to interpret behavioural and emotional data, enabling real-time insights