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for Multi-Agent Decision-Making, https://oceanerc.com ). This timely project will develop statistical and algorithmic foundations for systems involving multiple incentive-driven learning and decision-making
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achieved by combining state-of-the-art algorithms from multiple domains such as evolutionary algorithms, reinforcement learning, and control theory. The main responsibility of the successful applicant will
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organisational and time-management skills, with the ability to manage multiple tasks. The ability to work both independently and as part of a collaborative team, often across disciplines. A demonstrable interest
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individuals who have: Strong organisational and time-management skills, with the ability to manage multiple tasks. The ability to work both independently and as part of a collaborative team, often across
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multiple disciplines and national institutions. What you will do Leadership: Lead diverse AI projects, adapting your approach to meet the specific needs of clients and teams. Community engagement: Lead
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conditions. Our work combines traditional statistical methods with advanced artificial intelligence algorithms to identify patterns in disease. We also use qualitative methods to understand lived experiences
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will include contributing to our clinical NLP tools, algorithms and interfaces used by clinical specialists. The post holder will be expected to be able to contribute in the following areas: Extend our
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network performance across multiple layers and levels of abstraction The ideal candidate will possess strong expertise in quantum communication and networking, with a solid command of both theoretical
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contributing to our clinical NLP tools, algorithms and interfaces used by clinical specialists. The post holder will be expected to contribute to: Extend our software platforms for electronic healthcare record
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-resource settings. This project aims to achieve several objectives, including the development of a new AI-algorithm and a paired dataset for comparing how different imaging techniques influence