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) information-theoretic active learning, and c) capturing uncertainty in deep learning models (including large language models). The successful postholder will hold or be close to the completion of a PhD/DPhil in
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will disrupt today’s most vibrant research frontiers: Embed model-based AI into self-supervised pre-training pipelines Finetune multimodal deep learning models that answer diagnostic questions about X
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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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data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms to understand
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laser processing and to bring your ideas in AI/ML to the technology level. You have a solid background in programming (deep learning, reinforcement learning, etc.), electronics, high-speed data
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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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on applying, developing and implementing novel statistical and computational methods for integrative data analysis, causal inference, and machine/deep learning with GWAS/sequencing data and other types of omic
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., 2019; Pedersini et al., 2023). We combine ophthalmological, neuroimaging and behavioral data, and incorporate deep learning methods to facilitate biomarker discovery and enhance predictive power. As a