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Field
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algorithm development, modeling machine learning, and scientific simulation ▪ Ability to work well in an interdisciplinary environment, and to collaborate with experimentalists ▪ Strong oral and written
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PROGRAMME AND TRAINING: - extend the knowledge of the state of the art in machine learning for lung cancer imaging data; - identify and select the appropriate methods for the study in question; - develop
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testing of machine learning/AI algorithms Integration of radiomic and biological datasets Working closely with Medical Physics colleagues on reviewing recommendations for detection of specific metabolites
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tier conferences and journals in data mining/machine learning, Artificial Intelligence in Education and Educational Data Mining, Human-Computer Interaction strong technical expertise in data mining, data
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their work through cataloging and documentation, preventive care, processing loans, storage, and facilitation of storage and object access, while receiving hands-on training in professional collection
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of machine learning, simulation-driven testing, and iterative calibration based on real-world datasets. Contribute to scholarly publications, technical documentation, and progress reports required by funding
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in conducting human behavioural experiments or human-centered field studies. Demonstrated experience in using machine learning, such as deep learning for image processing, or natural
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experience in natural language processing, sound-based machine learning, development and deployment of health technology software . interest and previous experience in collaboration with inter-disciplinary
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looking for postdoctoral researchers in the area of computer vision, AI, and machine learning. The initial appointment will be for 2 years with a possible extension with a tentative start date in January
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programming languages such as Python and C++, as well as experience with machine learning frameworks like TensorFlow or PyTorch Familiarity with image processing libraries and a solid grasp of deep learning