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are demonstrated knowledge related to acoustic modelling, measurement and soundscape. o Essential are demonstrated data analytic skills, ideally with machine learning or statistical modelling • Other general
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integration and AI models tailored for fish behaviour, health, and stress signal analysis. Investigate and apply novel machine learning and deep learning techniques for pattern recognition, classification, and
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researcher in natural language processing and large language models to work with a team from multiple disciplines of machine learning and artificial intelligence to develop multimodal large language models
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: Develop novel machine learning theories and techniques for analyzing noisy time-series data, with a particular focus on seismic signals Perform uncertainty quantification in time-series analysis to assess
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updates to principal investigator and funding agency Report writing/presentation Job Requirements PhD degree in an engineering field related to this project Experience in dynamic modeling, machine learning
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optimization of multi-modal LLMs. Investigate and implement methodologies to ensure AI authenticity, accountability, and the integrity of digital content. Develop and refine machine learning and deep learning
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areas. Key Responsibilities: To independently undertake research in computer vision and machine learning. To produce research reports and/or publications as required by the funding body
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and technological disclosures writing. Job Requirements: PhD in Computer science, Computer engineering, or related field. Experience in privacy-preserving techniques’ research and implementation. Strong
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into operational use cases. Prepare data collection frameworks and work on fish health monitoring datasets for machine learning training and benchmarking. Support the development of translational “lab-on-farm
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: A PhD in Physics, Computer Science, Mathematics, Machine Learning or relevant fields. Strong publication record in top conferences/journals, such as Nature Physics, Nature Communications, PRL, T-PAMI