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signals and initiate downstream responses, with a particular emphasis on the mechanistic basis of activation and small molecule modulation. We investigate pathways involving cytosolic DNA sensors
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. The consortium behind ArcSolution is a highly qualified and diverse team, consisting of 14 partners from 8 different nations, from a range of geographic regions, including the Arctic and other key areas
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(QMUL). The researcher will be working under the supervision of Prof. Matteo Palma (QMUL): see http://research.sbcs.qmul.ac.uk/m.palma/. We have developed different nanohybrids platforms interfacing low
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Nanomaterials that detect protein-structural changes Nano-optical devices for protein-signal sensing AI algorithms for protein structure and dynamics prediction Outstanding Postdoctoral Training Strategy
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available single-cell sequencing data generated from patient samples and mouse models, we will enhance and apply machine-learning based algorithms to deconvolute bulk tumor RNA-seq samples to distinct immune
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efficient decoding algorithms" supported by the Luxembourg National Research Fund (FNR). The APSIA Group is seeking a highly qualified post-doctoral researcher for this project. For further information, you
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electrophysiology, calcium imaging, optogenetics, animal behavior is preferred, but we are interested in applicants with different backgrounds Background in data analysis, image processing, physics, engineering are
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and exciting research opportunities for scientific inquiry. Overall, the distinct areas of investigation for the Grant and the Sengupta labs allows the ideal candidate to acquire and develop different
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vision, IoT sensors, and blockchain to monitor food quality, safety and animal welfare in real-time and enhance transparency. AI and machine learning will analyse data from pilot sites to identify
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interdisciplinary teams to apply developed algorithms to real-world datasets and generate valuable biological insights. Perform integrative analyses of multidimensional datasets within the context of basic immunology