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Field
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to humans and are accessible to algorithmic techniques while neural models are adaptive and learnable. The aim of this project is to develop models which combine these advantages. The project includes both
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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
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conduct cutting-edge research on topics including, but not limited to: Complexity theory Quantum algorithms and complexity Sublinear algorithms Interactive proofs, PCPs, and zero-knowledge proofs
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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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Your Job: Quantum computers will play a crucial role in the development and optimization of battery materials in the future. In this project, you will develop innovative quantum algorithms
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the fundamental limits of quantum error correction (QEC) while concurrently advancing efficient decoding algorithms for quantum error-correcting codes in the near-term, noisy intermediate-scale quantum (NISQ) era
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generate, transmit, and detect OAM-entangled photons under realistic atmospheric turbulence. Deep learning algorithms will be employed to pre-compensate distortions in real time, maximizing state fidelity
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the area of enzyme engineering to the next level, while having a positive impact on our world. When joining our group, you get the opportunity to use the latest algorithms in machine learning for improving
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | about 1 month ago
to be carried out focus on the daily operational activities of home hospitalization units, with the goal of developing optimization models and algorithms to support the planning of routes, schedules, and