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through multi-modal sensing, autonomous UAV platforms, and advanced AI-based analysis. A central focus is the detection of defects in bridges and viaducts using X-ray, LiDAR, visual and acoustic data
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Low-Cost Sustainable Materials to Mitigate the Impact of Taste and Odour Compounds from Algal Blooms
compounds from water. This will involve setting up methods for the analysis of selected taste and odour compounds; characterising the properties of selected low-cost adsorbents (e.g. seaweed, sawdust and
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projects integrating omics, clinical and medical imaging data, contributing to biomarker identification and the development of computational approaches for healthcare. Key responsibilities include analysis
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evaluation of modal-decomposition techniques applied to data from high-fidelity numerical simulations of landing-gear aeroacoustics. The researcher will develop and implement modal-decomposition methods using
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metagenomics), environmental geochemistry and mineralogy, bioinformatics for DNA sequence analysis. The candidate should have a taste for team and interdisciplinary work and be familiar with the latest
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, as well as from industry. For more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job/294560/phd-research-fellow-in-deep-learning-for-medical-imaging-and-multi-modal-data-in
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Position Details Position Details Job Title RESEARCH ASST II Position Number 8151024 Work Modality Fully In-Person Is this request for the creation of a new Position (or the modification
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: Commensurate with education and experience. Benefits Provided: Contract Required Attachments: Resume, Cover Letter Job Description --- Deploys training curriculum through various learning modalities including
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an emphasis on technology, data science and the humanities. For more details, please view https://www.ntu.edu.sg/medicine . We are looking for a Research Fellow to conduct AI for medicine research. The role
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, to join our team! We are located at the Department of Biomedical Informatics (https://www.chiragjpgroup.org/members.html ), Harvard Medical School, with affiliations with the Harvard Data Science Institute