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mission. You will: Help collate data resources relevant to suicide and self-harm. Develop new machine learning methodologies (from artificial neural networks, decision trees, evolutionary algorithms and
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) To develop Deep Learning algorithms to significantly speed up probabilistic inference algorithms of current spatial birth-death models 2) To incorporate fossil stratigraphic and spatial information into a new
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and significant piece of information to the right point of computation (or actuation) at the correct moment in time. To address this challenge, you will focus on developing theoretical and algorithmic
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for photocatalytic degradation and H2 production.Designing multi-objective optimization algorithms to maximize environmental and economic performance. Your RoleAs a PhD researcher, you will: Build and validate hybrid
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. The ML will use 500,000 fundus images from open-source and customised retinopathy datasets. We will compare retinopathy grading accuracy by NHS clinician vs ML algorithm. This will build on Exeter’s
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PhD Studentship: Distributed and Lightweight Large Language Models for Aerial 6G Spectrum Management
: Algorithm Validation and Use Case Demonstration (Months 27–36): This WP will first develop an integrated hardware–software testbed to systematically validate the performance of proposed solutions under
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expand current technology to include automated live analysis, integrating machine learning algorithms capable of interpreting the complex behavioural patterns of mussels in response to environmental stress
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of federated algorithms that enable fair management of the advantages and duties of energy communities in which vulnerable people live. The automatic generation of data models using AI technology will enable
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, algorithmic, and real-time implementation framework for on-the-fly autonomy in crowds. The resulting methods will (i) adapt to unpredictable human interactions that introduce high levels of uncertainty, (ii
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responsibilities include: Development of a flood classification framework for flood type prediction Comparison of different ML algorithms in a sensitivity study Communication with stakeholders Development of open