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Field
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Hope. To accelerate the development of new therapies, we leverage City of Hope’s unique in-house GMP manufacturing capabilities for cell therapy (CAR-T cells, stem cells, etc.), monoclonal antibodies
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bring expertise in computational methods (such as machine learning, chemo-informatics, molecular dynamics simulation, structural biology) and / or experimental methods (such as biophysical analysis
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to facilitate the integration of the framework with external systems and educational platforms; Establish a Machine Learning Operations (MLOps) pipeline to automate the lifecycle of models, including training
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, analysis and evaluation, and writing reports which contain descriptive, analytical and evaluative content. The purpose of this role is to acquire the professional skills needed to pursue a career path of his
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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mathematics, computer science, electrical engineering, machine learning, optimization, statistics, etc.) and specific domain area. Finalists will be paired with mentors by the search committee, facilitating a
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participate in democracy, our centre tackles the promise and peril of hybrid intelligence—human and machine working and learning together. AI LEARN’s mission is to establish an internationally leading
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analyzing numerical methods and/or machine learning methods for scientific computing. A strong computational background and experience with languages and frameworks such as Matlab, Python, NumPy/SciPy
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of cellular behavior to advance gene and cell therapies — including CAR-T cell therapy and muscle stem cell regeneration. The successful candidate will apply machine learning, statistical modeling, and single
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, work and participate in democracy, our centre tackles the promise and peril of hybrid intelligence—human and machine working and learning together. AI LEARN’s mission is to establish an internationally