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, computer-aided decision support systems Previous experience with using deep learning models (e.g., convolutional neural networks, autoencoders, transformers) for academic research Documented experience in
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software such as recommendation systems, computer-aided decision support systems Previous experience with using deep learning models (e.g., convolutional neural networks, autoencoders, transformers
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. DVXplorer), and tactile/force sensors. Strong background in computer vision and deep learning, with practical implementation experience. Proficiency in programming with C++ and Python, including use of ROS
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qualified in relevant subject area (or nearing completion) Good knowledge of computer vision algorithms for image and video processing Strong experience in machine learning or deep learning for medical image
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-dose IL-2 affects the neuro-inflammatory process. You'll use advanced cellular immunology techniques to conduct deep phenotypic and functional characterisation of regulatory T cells (Tregs), establishing
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). About the role The project's primary goal is to investigate how low-dose IL-2 affects the neuro-inflammatory process. You'll use advanced cellular immunology techniques to conduct deep phenotypic and
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datasets Proficiency in Python for data science and machine learning Possess sufficient breadth or depth of specialist knowledge with deep learning architectures including generative models, particularly
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bioinformatic workflows. Familiarity with biomedical ontologies and text mining on Electronic Health Records and biomedical literature Knowledge of machine learning / deep learning with an interest in