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. For example, investigating costs and benefits related to the adoption of state-of-the-art technologies that permit tracking and chain of custody. The team will also explore machine learning and artificial
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Glimpse of the Job The Postdoctoral Research Associate will perform independent research activities requiring an advanced level of knowledge in a field of science or learning. This work is predominantly
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against simpler machine-learning baselines; • train and evaluate ARCA on large-scale microbiome datasets, with attention to sparsity, batch effects, scalability, generalisation across studies and
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that prioritise student learning in the age of AI. Job requirements You hold a PhD in Educational Science, Learning Sciences, Social and Behavioural Sciences, Engineering Education, Human-Computer Interaction or a
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 9 hours ago
motivated candidate with a strong interest in machine learning and clinical neuroscience. The lab studies resilience and vulnerability in brain aging and dementia, and builds computer-aided methods and tools
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working towards a shared goal. You will be responsible for the design and pilot testing of machine learning-based automated ultrasound video analysis models that incorporate temporal reasoning. The research
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checks with advanced machine learning architectures, specifically Long Short-Term Memory (LSTM) networks and Variational Autoencoders (VAEs). The researcher will use historical QC archives dating back
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start date. Preferred Qualifications: Research experience in computer vision, NLP, geospatial data systems, or high-performance computing. Brief Description of Duties: The Postdoctoral Associate will
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analysis, machine learning, mathematics of data scienceMathematical modeling and manifold learning of high-dimensional data geometry, with theoretical foundations and applications in evolutionary biology and
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analyse electrochemical free-energy landscapes and connect elementary-step energetics to catalytic performance apply machine-learning interatomic potentials and microkinetic models where appropriate