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devices Develop hardware-aware machine learning models incorporating electronic and optical device constraints Design and implement hardware-efficient training methodologies for machine learning systems
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. This field encompasses Computer Science, Data Science, Artificial Intelligence, and related interdisciplinary areas, with a focus on computing technologies, software development, algorithm design, and
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technologies, software development, algorithm design, and data applications. Discipline, including, but not limited to: Computer Science and Technology, Cyberspace Security, Data Science and Big Data Technology
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. The MPOG team includes clinicians, quality improvement experts, software developers, statisticians, and administrators. For more information, please visit https://mpog.org/about/ Position Summary
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scientists, biomedical informaticians, clinicians, and public health researchers to develop deployable, trustworthy methods that improve patient outcomes and health system operations. Key responsibilities
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Head and Neck cancer patients. This person will be working with our multi-disciplinary cancer specialty clinics and tumor boards. This individual will be expected to develop algorithms around national
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matter expert offering support, training and guidance relative to the discipline/area. May participate and/or present on the research developed, or the established work of those within the department. FIVE
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developed involves continuous analysis of the state of the art, the definition and specification of technical and functional requirements, as well as the design of data models, synchronisation algorithms and
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: Python programming Bash programming Familiarity with genomic data Notions of algorithmics Experience with back or front-end web development is a plus Soft skills : team spirit ease in communication
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in the Phi_Lab, led by Dr. Azeem Ahmad, and will focus on the development of advanced reconstruction algorithms and next-generation quantitative optical microscopy and tomography systems for imaging