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Field
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health records (EHR), waveforms from bedside monitors, radiology images and wearable sensors. This position offers a unique opportunity to work closely with clinicians on applications of machine learning
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will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep learning-based computer vision algorithms and software for object detection, classification, and
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PROGRAMME AND TRAINING: - extend the knowledge of the state of the art in machine learning for lung cancer imaging data; - identify and select the appropriate methods for the study in question; - develop
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their work through cataloging and documentation, preventive care, processing loans, storage, and facilitation of storage and object access, while receiving hands-on training in professional collection
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experience in natural language processing, sound-based machine learning, development and deployment of health technology software . interest and previous experience in collaboration with inter-disciplinary
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-seq datasets, and applying advanced statistical and machine-learning methods (AI/ML) to extract novel biological insights that drive our translational and fundamental research programmes. In
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in conducting human behavioural experiments or human-centered field studies. Demonstrated experience in using machine learning, such as deep learning for image processing, or natural
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researcher in natural language processing and large language models to work with a team from multiple disciplines of machine learning and artificial intelligence to develop multimodal large language models
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tier conferences and journals in data mining/machine learning, Artificial Intelligence in Education and Educational Data Mining, Human-Computer Interaction strong technical expertise in data mining, data
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projects across the following areas: Spatial and Single-Cell Proteomics in Childhood Cancer Cell-cell communication & cellular fitness in CAR-T & CAR-NK therapy Deep learning & LLMs in mass spectrometry data