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Background in machine learning or deep learning methods, including Graph Neural Network (GNN) Experience with Large Language Models (LLMs) applied to biological data collection, extraction, and standardization
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The Section for Electrical Energy Technology at the Department of Electrical and Computer Engineering (ECE), Aarhus University, is in a phase of rapid growth in both education and research
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contribute to the advancement of knowledge in crystalluria. We have links with The Newcastle upon Tyne Hospital groups and with large groups based in the prestigious Bernal Institute in Ireland. This project
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to manage, organize, and back up large amounts of image and tabular data generated by program and collaborator labs. Other Requirements: -May have to work on the weekend and/or after normal hours. -Travel is
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public health. In this role, you will develop and evaluate novel AI and machine learning methods using large-scale multimodal datasets, contributing to epidemiology-informed foundation models, predictive
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extreme weather forecasting, employing data science models as developed in computer vision and natural language processing (NLP). This project leverages the large-scale high-performance computing (HPC
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skills and strong publication records to apply. Some skills in analyzing/evaluating large data sets are highly desirable. Knowledge of an advanced programming language such as MATLAB, Python, etc. is
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cultural activities; and more! The University of Arizona has been recognized for our innovative work-life programs. For more information about working at the University of Arizona and relocations services
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spatial transcriptomic data. A demonstrated interest in data visualization and large-scale data analysis is highly desirable. The ideal candidate will have a keen interest in understanding complex
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systems routinely handle data rates of several GB/s and support large-scale scientific data workflows. To support sustainable data management at next-generation photon science facilities, we are seeking a