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generating, mobilising, and harvesting “big data” to create a dynamic and agnostic collection of information and deliver a new class of research that will enable a better understanding of the clinical
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generating, mobilising, and harvesting “big data” to create a dynamic and agnostic collection of information and deliver a new class of research that will enable a better understanding of the clinical
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Astronomy at Johns Hopkins University (JHU) invites applications for one postdoctoral fellow position to pursue research in time-domain multi-messenger astrophysics with emphasis on data science and AI
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, Saadiyat Island, United Arab Emirates [map ] Subject Area: Interdisciplinary Data Science and Artificial Intelligence Appl Deadline: none (posted 2025/07/31) Position Description: Apply Position Description
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Post Doctoral Researcher in Human-Centered AI for Software Engineering, Department of Electrical ...
The Section for Software Engineering and Computing Systems, at the Department of Electrical and Computer Engineering (ECE), invites applicants for a two-year postdoctoral position within the area of
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interpretation of atmospheric circulation in high-resolution reanalysis data, idealised model simulations and a state-of-the-art weather forecasting system. The post-holder will have the opportunity to teach
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for one year. The associate will have the opportunity to assist with data analysis and manuscript writing for a recently completed large randomized clinical trial on smoking cessation induction within a
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lives, one discovery at a time! Community Information Columbia offers small-town friendliness with big city features and a high quality of life for people of all ages and interests. Founded on education
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, epidemiology, biostatistics, genomics, big data analytics, or artificial intelligence analytics Be familiar with conducting analysis with different types of data, including metagenomics sequencing, genomics
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with the possibility of renewal. This project addresses the high computational and energy costs of Large Language Models (LLMs) by developing more efficient training and inference methods, particularly