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The LivePerson Centre for Speech and Language offers a 3 year fully funded PhD studentship to explore novel and innovative learning methods for construction of speech processing models. Domain
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decisions related to turbine inspection and maintenance with a human expert [4, 5]. This can be based on a deep reinforcement learning framework, which interactively optimises key performance indicators in
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Sintorn, Professor in digital image processing, at the Department of Information Technology and conducted alongside researchers developing computational methods with a particular focus on deep learning and
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PhD positions in ML-guided directed evolution (3.0 FTE) (V25.0085) « Back to the overview Job description Are you passionate about combining the directed evolution of diverse biomolecules with deep
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spectrum, in topics in virology and immunology, and currently specializes in computational biology focusing on developing methods and applications of deep learning for protein sequence and structure, as
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to achieve, at least a 2.1 honours degree or a master’s in a relevant science or engineering related discipline. Applicants should have strong background in Machine Learning and Deep Learning. To apply, please
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the challenge of time-consuming sideshaft testing. As a key member of the team, you will apply cutting-edge machine learning and deep learning techniques to dramatically reduce testing cycles. You will lead life
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conceptual background in cellular immunology. Interest in, and ability to, learn bioinformatics. To apply, please submit the following documents to Prof. Magdalena Plebanski (magdalena.plebanski@rmit.edu.au
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, within the Centre for Image Analysis at the Department of IT and conducted alongside researchers developing computational methods with a particular focus on deep learning and image analysis. The project
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FAU DCN-AvH. Chair for Dynamics, Control, Machine Learning and Numerics | Germany, | Germany | 3 months ago
by Prof. Enrique Zuazua , invites applications for two (02) PhD research positions at the ERC CoDeFeL , Control for Deep and Federated Learning project. DEADLINE: Wed. March 25, 2025 Position Details