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Field
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of others, providing expert advice and guidance. Skills, Experience & Qualifications Needed A first degree in physical / engineering /architecture and a PhD in pollution and/health. Experience in sensors
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for this Research Fellowship will have a strong background in a relevant discipline, including but not limited to anthropology, sociology, urban studies, architecture, history, environment and ecology, science and
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integrates custom neural architecture design, simulations, and publicly available genomic datasets to develop new inference methods. The Postdoctoral Associate will conduct research related to creating
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knowledge of experience with python and modern machine learning architectures (e.g. VAEs, transformers) and libraries (e.g., numpy, pytorch or tensorflow or JAX frameworks). A4 Knowledge of mathematical
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microservices architecture and Kubernetes. Knowledge of AWS, Terraform, and other cloud technologies Work Ethic: A strong work ethic with the ability to work independently and as part of a broader team, including
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results. Preferred Qualifications: Experience with generative AI deep learning and active involvement in data science and machine learning projects. Experience in neural network architecture, cloud
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multimodal data, dynamic updates, and scalable semantic interoperability in large-scale DPP systems. Particular emphasis will be placed on Representation Learning techniques, Transformer-based architectures
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understand plasmadynamics and hypersonic flow physics, and 2) the exploration of transformational concepts for in-space power and propulsion using innovative laser architectures and/or rarefied atomic beams
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architectures”. Qualifications For the post of Postdoctoral Fellow, applicants should have a doctoral degree or an equivalent qualification and must have no more than five years of post-qualification experience
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for complex scientific problems Designing algorithms to improve the performance of scientific applications Researching digital and post-digital computer architectures for science Developing and advancing