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thinking around the development of school culture Model instructional coaching Collaborate on monitoring systems Facilitate thinking around professional learning supports to staff Facilitate problem solving
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biomedical and clinical data. The Centre works at the interface of data science, machine learning, computational biology, epidemiology, and clinical research, with the goal of transforming research models
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motivation Testing whether the system performs equitably across cultural and language groups Training spans intervention design, trial methodology, human-computer interaction, and applied machine learning
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and electrodermal activity (EDA). Developing, implementing, and evaluating machine learning and AI models using public and project-generated datasets. Applying data-centric AI techniques, including data
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will be responsible for the follow : (full details of duties available from the Job Description) Research Collaboration and engagement You will have completed a PhD in machine learning, computer science
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Group Leader and Professor AI in Biology - Dept of Computer Science and Dept. Electrical Engineering
but are not limited to: development of new AI architectures for biology and hybrid models that combine deep learning with mechanistic models; foundation models of genome regulation using single-cell and
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projects including research related to ALS, Alzheimer's disease, and brain metabolism. Work will involve cellular and/or mouse models depending on the project. Dr. Walther is deeply committed to mentorship
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, ECG, GSR and other biosignals. Multimodal data analysis Machine learning and advanced statistical modeling Research experience in perception, consciousness, cognition, or emotions will also be valued
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requirements for this position include regularly sitting at a computer workstation for extended periods of time with repetitive motion (such as typing); occasionally pushing, pulling, and/or lifting objects up
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surveys and subsequent development and implementation of artificial intelligence and machine learning analytical pipelines to efficiently process resulting datasets to estimate indices of fish abundance