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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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Code 9791AO Employee Class Acad Prof and Admin Add to My Favorite Jobs Email this Job About the Job Job description: 50%: Lead and conduct research in the development and application of algorithms
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to make a difference. Do you want to be involved and contribute to our development? Together, we can create a sustainable future through knowledge and innovation. We believe that knowledge and new
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of the recruitment and description of the project] * Background of the recruitment and description of the project Artificial Intelligence is a field that focuses on the development, evaluation, and application
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typologically diverse languages Creating self-supervised learning algorithms that can assess phonological development and speech complexity in children from birth through age 6, with applications to both typical
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candidates will have specialist knowledge in signal processing and algorithm design, with experience in machine learning, AI system development and reinforcement learning along with a strong publication record
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, and interdisciplinary research team, RE will develop and implement deep learning algorithms to analyze trap camera footage for wildlife monitoring and conservation efforts. Job Responsibilities
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | about 4 hours ago
the replicator equation. The candidate(s) may also be required to develop computational and algorithmic platforms to link models to biological data. The project integrates dynamical systems, graph theory, linear
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School graduates over a thousand students who are ready to take on great ambitions and challenges. For more details, please view: https://www.ntu.edu.sg/eee We are looking for a Senior Research Fellow to
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Application deadline: 30/04/2026 Research theme: Nuclear Engineering How to apply: https://uom.link/pgr-apply-2425 This 3.5-year PhD project is fully funded; home students are eligible to apply