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School of Engineering Sciences in Chemistry, Biotechnology and Health at KTH Project description Third-cycle subject: Biotechnology The project aims to develop probabilistic deep learning models
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Deepfakes, derived from "deep learning" and "fake," involve techniques that merge the face images of a target person with a video of a different source person. This process creates videos where
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This project aims to advance representation learning in cybersecurity by developing deep learning architectures capable of extracting high-level, structured, and semantically meaningful representations from
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identification framework. The role involves developing a species-agnostic computational pipeline that integrates cutting-edge deep learning methods - such as AlphaFold2 and FoldSeek -to enhance protein function
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project at the forefront of microscopy and bioimage analysis (https://www.msca-agile.eu/ ) and contribute to OMERO integration and optimization of Biom3d, a cutting-edge deep-learning framework for 3D image
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will design and validate advanced multi-agent Deep Reinforcement Learning (DRL) and/or Digital Twin (DT)-enabled methods for efficient, scalable and time-critical handover optimisation. The work will
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Wee Kim Wee School of Communication and Information Nanyang Technological University, Singapore Part-Time Lecturer for IN6242 Deep Learning Foundations We are seeking a part time lecturer to teach
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candidates will be involved in projects exploring novel ways to incorporate topological structures into deep learning pipelines, contributing to both theoretical advancements and practical applications
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conditions (Burgard et al., 2022). The application of deep learning to this problem has yielded promising results (Rosier et al., 2023; Burgard et al., 2023). Further development and refinement
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