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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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Computational Astrochemistry/Algorithm development for Quantum Dynamics Calculations School of Mathematical and Physical Sciences PhD Research Project Self Funded Prof AJHM Meijer Application
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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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Interplay between Algorithms and Combinatorics
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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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About us: We are seeking experts in medical image deep learning to join our team and help develop novel computationally efficient segmentation algorithms. We welcome application from individual with
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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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at the interface between computational design and in vitro experiments, the team has developed multiple in silico and in vitro methods to design novel antibodies and nanobodies as therapeutic agents and research
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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