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into company valuations. You'll apply cutting-edge machine learning techniques (transformer models, causal forests, double machine learning) to understand which aspects of patent language predict valuable
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interactions, and mobility are collected). Machine Learning models will be trained to infer fatigue in real time, triggering adaptive prompts, such as suggesting micro-breaks. Expected outcomes include a sensing
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for stress-testing. Training spans multi-agent reinforcement learning, evolutionary computation, adversarial machine learning, game-theoretic modeling, and financial crime compliance. You will design agent
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to compliance professionals for validation studies. Training spans advanced NLP (transformer fine-tuning), financial crime typologies, privacy-preserving machine learning, and product-oriented development. You
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, biodiversity monitoring, and climate resilience. The work supports strategic priorities in Environmental Sciences, Software/Cyber. PhD researchers will explore how AI-driven Earth observation, computer vision
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. The successful candidate will join the Intelligent Systems Research Centre (ISRC) at Ulster University’s Magee campus, working with experienced researchers in machine learning and cognitive analytics
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in exercise and dance interventions. Build and evaluate AI / machine learning models using labelled, collected multimodal data to classify motor and non-motor symptoms, identify digital biomarkers
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vast amounts of rich, complex data, unlocking their insights requires cutting-edge AI and machine learning (ML) techniques. Meanwhile, although artificial neural networks (ANNs) have powered recent AI
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and machine learning techniques for the design of superconducting qubits, one of the leading qubit modalities used in today’s quantum computers. The optimal design of superconducting qubits is a highly
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- 2025 - Business Strategy and the Environment - Wiley Online Library Additive Manufacturing: A Comprehensive Review Big data, machine learning, and digital twin assisted additive manufacturing: A review