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materials systems at the molecular level with machine learning. The PhD Student will work with tumour sections to develop multiple instance learning and weak supervision / spatial transcriptomics models
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machine learning for next-generation wireless networks, (ii) Foundations of semantic communications and age of information, (iii) Stochastic geometry and spatial modeling of large-scale wireless systems
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scholarship, in partnership with the Australian Office of National Intelligence, will be awarded to an outstanding applicant interested in connecting spatial and spectral information to understand complex
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Biosafety Lab Alabama Birmingham (SEBLAB) having BSL-3 laboratories, ABSL-3 animal facility, high-parameter flow cytometry and cell sorting cores, and UAB's nationally recognized spatial omics and proteomics
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Multiple PhD Scholarships available - Cutting-edge research at the frontiers of Whole Cell Modelling
Multiple PhD Scholarships available - Cutting-edge research at the frontiers of Whole Cell Modelling Job No.: 683222 Location: Clayton campus Employment Type: Full-time Duration: 3.5 to 4-year fixed
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” and “Smart Mobility” (Google Scholar), he has received multiple prestigious international awards, including the IEEE CASE Best Conference Paper Award, INFORMS QSR Best Student Paper Award, and INFORMS
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Thebault labs are seeking a skilled and motivated Research Assistant to support data analysis and pipeline development for cutting-edge research in neuroinflammation, multiple sclerosis, and
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Position Description The Unsteady Flow Diagnostics Laboratory (UNFoLD) led by Prof. Karen Mulleners at EPFL in Lausanne is looking for multiple PhD students to join the group in the fall of 2025 or early
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development and marine management. Your primary tasks will be to: Compile and harmonize data from multiple sources (e.g., EMODnet, Copernicus, fisheries surveys, citizen science). Engage with data managers and
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to the collected dataset. Deep learning will focus on physics-based features developed earlier. Convolutional layers will be used to extract spatial patterns, while LSTM layers will capture temporal aspects across