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with expertise in the following four areas: (1) working with large-scale digital trace data; (2) building and running natural language processing and machine learning workflows; (3) experimental design
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expertise spanning the full breadth of operations research, including large-scale optimization, applied statistics, military logistics, warfare analysis, and critical infrastructure resilience. Our students
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systems, large multimodal foundation model training and/or finetuning, and continuous learning pipelines. Experience in multi-modality data analysis (e.g., image, video, text). Experience working in
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of machine learning to the practical tools of deep learning, now available through modern foundation models. For the theory part, the selected candidate will work in close collaboration with
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on the career stage), in any area of psychology. In line with our strategic priorities, we are particularly keen to appoint colleagues with strong statistical expertise (big data, longitudinal
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a form suitable for quantum computing, calling for a cost-benefit analysis of quantum machine learning algorithms. To address scalability for large datasets, lossy data compression is often
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energy consumption in information processing and machine learning (e.g., arXiv:2308.15905); Quantum phenomena in information processing: exploring how quantum effects can be utilized to process information
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, Technology and Information in Human-Computer Interaction (HCI), with a focus on responsible computing. The successful candidate will have an interest in online safety, including areas such as social media
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preferential viewing behavior, using large-scale electrophysiology, behavioral experiments, and computational modeling. We welcome applications from recent PhD graduates who are interested in these or related
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PhD Stipend/Integrated Stipend in representation, compression, learning, and inference for classical and quantum data. At the Technical Faculty of IT and Design, Department of Computer Science, one