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Vision, Robotics, Evolutionary Computation, Deep Reinforcement Learning, and Machine Learning. This should include a proven publication track record. You should also have: Research Associate: A PhD (or
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be the state estimation of the robotic system from external cameras. Familiarity with existing methods from these domains, such as Deep Learning, Quality-Diversity algorithms, reinforcement learning
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recently completed (or be close to completing) a PhD in Computer Science, Machine Learning, Natural Language Processing (NLP), or a related field, with a thesis focused on AI, specifically LLMs
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, band selection Heterogeneous network architectures, including terrestrial and non-terrestrial networks Deep learning for wireless communication problems, particularly in areas such as spectrum management
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qualifications include: Experience with radio interferometric observing, data processing, and imaging. Experience with modern machine learning / deep learning techniques and software packages. Experience with time
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timings) affect the metabolome and proteome of rapeseed seeds. Your findings will serve as molecular fingerprints to support Deep Learning models for hybrid development. Whom we are looking for: An early
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Free probability theory High-dimensional probability, concentration and functional inequalities Mathematical aspects of machine learning and deep neural networks Free Probability aspects of Quantum
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-dimensional probability, concentration and functional inequalities ? Mathematical aspects of machine learning and deep neural networks ? Free Probability aspects of Quantum Information Theory. While excellent
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successful candidate will possess skills in natural language processing and deep learning. Experience of studying the robustness and generalisability of LLM would be beneficial. This is a full time post (35
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responsibilities Design, implement and benchmark deep machine learning models for large-scale cancer datasets that include genomics, transcriptomics, epigenomics and imaging data Collaborate closely with