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Field
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Analysis for Stable AI” funded by a European Research Council Advanced Grant. The Opportunity: This postdoctoral position will be devoted to research on algorithms in Artificial Intelligence (AI) from
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of algorithms for natural language understanding, structured command generation, and domain-specific model adaptation or fine-tuning. Integrate NLP and speech technologies (ASR/TTS) into a unified tactical signal
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models optimised with evolutionary algorithms to address combinatorial optimisation in model design and the noisy nature of climate data. The Doctoral Researcher will receive on-the-job training in machine
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creating robust, low cost, and real-time edge-AI algorithms capable of accurately classifying diverse marine species and debris under complex and dynamic underwater conditions. The demand for such a low-cost
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with key Analysts and the Research Data & Evidence team you will be responsible for managing work areas from the design and development of funding algorithms and quality assurance processes to delivery
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-terminal antennas and beamforming operating in FR1 bands and future FR-2, enabling robust terrestrial–satellite integration for safety-critical air mobility services. To develop AI-based algorithms
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of expertise for this position are: (1) Software Engineering (2) Computer Architecture and Operating System (3) Programming and Algorithms. Additionally, knowledge of Artificial Intelligence and Machine Learning
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. Exposure to neural-symbolic algorithms for transforming intent into conformant security or safety policy and/or enforcing security controls is optional but beneficial. Research will also give the opportunity
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implementing AI algorithms to deliver safer and more efficient care. The student will have access to a unique training programme in AI in healthcare and health data science as well as a wide range opportunities
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qualifications will be considered. Experience of using machine learning algorithms and toolsets, ideally in a research context. Strong programming skills (e.g., Python, Java, C++) An interest in physiological