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visual and auditory cortices using techniques such as cross-modal decoding, unit reliability analysis, and shared variance component analysis (SVCA) Create comprehensive data visualisations and perform
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tackles fundamental challenges in multimodal representation learning by developing novel approaches to align distinct embedding spaces from speech and sign language modalities. Sign languages encode
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understanding of protein systems. As a PhD student, you will: Design and perform fluorogenic and nano-photonic DyeCycling experiments. Write/adapt analysis code to process fluorescence trajectories and extract
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, you will: Design and perform fluorogenic and nano-photonic DyeCycling experiments. Write/adapt analysis code to process fluorescence trajectories and extract kinetic information. Evaluate bioconjugation
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: Framework Development: Design and implement a generative deep learning framework for cross-modal integration and analysis, resilient to distribution shifts. Correlation Discovery: Identify interpretable
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characterizing defects such as dislocations Applying generative models (e.g., GANs, diffusion models) to augment microscopy datasets Investigating domain adaptation techniques across different imaging modalities
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communication environments. For the advertised PhD researcher position, this work involves written and multi-modal corpora development and analysis, and working with computational models of irony and analysis
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) to analyze data from the multi-modal Biological-Classification-of-Mental-Disorders (BeCOME) study, with a particular focus on the influence of environmental factors. REFERENCE NUMBER: 192 | 8748 The main focus
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, diffusion models) to augment microscopy datasets Investigating domain adaptation techniques across different imaging modalities Collaborating closely with experimental partners to validate methods and
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Thebault labs are seeking a skilled and motivated Research Assistant to support data analysis and pipeline development for cutting-edge research in neuroinflammation, multiple sclerosis, and