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to the development of remote sensing algorithms, simulation and modeling capabilities, and artificial intelligence/machine learning (AI/ML) methods in support of the goals of the joint NASA/USGS Landsat mission
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Entitled: “Covalent organic frameworks exhibiting thermally activated delayed fluorescence” Leader Dr inż. Jakub Ostapko The objective of this project is to develop and investigate a new class of self
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This postdoctoral position contributes to a UKRI-funded programme developing anatomy-driven artificial intelligence for translational neuroscience, with a focus on understanding how cognitive
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geoinformatics and spatial data science, including demonstrated knowledge of GIS, spatial analysis, spatial modelling, and GeoAI. Experience and expertise in WebGIS development, familiar with the core technologies
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antigens presented by MHC molecules. This curiosity-driven project develops cutting-edge AI technology for 3D TCR–pMHC modeling to improve neoantigen identification, TCR specificity prediction, and TCR
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understanding of parallel application development techniques (parallel programming models, algorithms, and software) Preferred Qualifications: Experience in implementing ab initio simulation codes such as VASP
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data driven approaches (experimental dataset physics based model dataset) to achieve process optimization, defect prediction and property prediction in various AM processes. The additional specific
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learning, and Earth sciences. We are seeking a highly motivated Postdoctoral Research Fellow to develop and apply innovative, data-driven models for seismology, with a focus on developing cutting-edge
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aspects of data collection, dataset preparation, software implementation, model validation, laboratory maintenance, cyberinfrastructure development, and documentation, depending on the role. Conduct
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occupancy estimation using eBird and acoustic detections Developing approaches for using eBird data to inform detection thresholds for acoustic detection models Developing approaches to convert acoustic