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of nondiscrimination is located at uab.edu/titleix . Department: Electrical and Computer Engineering Assignment Category: Full-Time Tenure Status: Non-Tenure Track Required Qualifications: Applicants must hold a PhD
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/or spatial genomics, computational biology, machine learning, bioinformatics, and systems neuroscience. Prior experience with deep learning applied to biological data is a plus. Practical experience
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. The research in the PhD project will focus on core spatio-temporal machine learning method development, including: generative models for grid-based and particle-based spatio-temporal data; controlled generation
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Low maintenance reliable main bearings for large wind turbines Offshore Wind CDT PhD Research Project Competition Funded UK Students Prof R Dwyer-Joyce, Dr Thawhid Khan, Mr Wooyong Song, Dr Siren
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application! We are looking for a PhD student in Statistics with placement at the Division of Statistics and Machine Learning, Department of Computer and Information Science. Your work assignments As a PhD
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, neuroimaging and clinical psychiatry, with direct clinical impact. Your main activities are: analyzing and integrating multimodal MRI data for biotype identification; applying machine learning and advanced
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) within the Department of Computer and Information Science . At STIMA we conduct research and education in both statistics and machine learning, at the undergraduate, advanced and PhD levels. We regularly
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Inria, the French national research institute for the digital sciences | Talence, Aquitaine | France | 20 days ago
Essential qualifications: Advanced degree (Master's or PhD) in Computer Science, AI, Machine Learning, or related field Demonstrated expertise in large-scale generative AI systems (inference and training
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large-scale speech and wearable data from participants in the GLAD Study cohort (https://gladstudy.org.uk/ ). Using large language models (LLMs) and acoustic analytics, they will uncover patterns in
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experiments, behavioral research, econometric and causal inference approaches, optimization and analytical modeling, and data-driven techniques such as machine learning and large language models. Our work is