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Field
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Responsibilities: The candidate will study theoretically forward and inverse uncertainty quantification problems for partial differential equations, and multiscale partial differential equations. He/she will develop
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neurodegenerative diseases. 5. Oncomechanobiology: this area focuses on mechanobiological basis of development, stem cells, and cancer, with the aim to discover new pathways of intervention in pathological conditions
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international collaborators across clinical, academic, and industry settings to develop privacy-preserving machine learning approaches, federated learning frameworks, and interpretable algorithms for multimodal
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Center for Devices and Radiological Health (CDRH) | Southern Md Facility, Maryland | United States | about 7 hours ago
on the development of optical models, image acquisition software, image processing algorithms, and deep learning algorithms using Zemax, Python, Matlab, LabVIEW, CUDA, and other programming environments. Training
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to join this development team as a fellow and learn to create, evaluate, and validate rapid, accurate, and sensitive diagnostic methods for detecting disease pathogens. The fellow will have an opportunity
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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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the design, development, deployment and evaluation of NeoShield’s applied machine-learning systems, the machine-learning-driven Clinical Decision Support Algorithm for neonatal sepsis and the real-time ward
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project - “Establishment of joint research centre on brain-inspired computing”. He/She will be required to: (a) conduct the research on the development of neuromorphic foundation models and brain
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-based methods to achieve personalised and novel outputs. This position will have a particular focus on developing fundamental AI algorithms and methods that can be used in systems for real-time creative
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analysis; (b) develop and implement algorithms for 3D perception (e.g. segmentation, localization and mapping); (c) design and execute experiments to evaluate, validate and refine algorithms and