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; Machine Learning• Clinical pathways and decision support for patients with acute chest pain• AutoPiX – Explainable Deep Learning for Multimodal and Longitudinal Imaging Biomarkers in Arthritis• Speaking
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, Statistics, Bioinformatics, Applied Math, or related field. MS or PhD degree is preferred but not required. Required qualifications ? Substantial expertise in training deep learning models and tuning large
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, and research team to ensure timely achievement of project deliverables. Undertake the following specific responsibilities in the project: i. Develop, train, and optimise deep learning models for object
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FieldMathematicsYears of Research ExperienceNone Additional Information Eligibility criteria The position requires a PhD in machine learning, NLP, causality, or a related discipline, with a strong command of deep
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Particle Acceleration is looking for a PhD Student (f/m/d) Multimodal Reconstruction of Laser-Electron Accelerator Phase Space using Physics-Informed Deep Learning. Your tasks Understand the physical process
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/deep learning with GWAS/sequencing data and other types of omic data, as in Mendelian randomization and TWAS. In addition to new methods development and evaluations, the job responsibilities include
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Doctoral Candidate in computer vision and machine learning for developing novel deep learning method
Machine Learning (DM3L) Doctoral Candidate in computer vision and machine learning for developing novel deep learning methods for satellite-based tracking of global CO2 and NOX emissions of point sources 80
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Machine Learning / Deep Learning / LLMs Other qualifications For the doctoral programme in question, the following are considered as other qualifications: documented knowledge within human-robot interaction
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experimental design. Proficiency with machine vision and deep learning techniques, including image segmentation, landmark placement and metric learning, for the automation of phenotypic analysis of large image
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. We welcome applicants with a PhD (or equivalent) in biostatistics, statistics, or a closely related quantitative field. We seek scholars with training in biostatistics/statistics and demonstrated