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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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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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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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-bandgap-key-future-green-electronics, https://c3nit.se/ Subject description The purpose of this project is to develop a data-driven approach for optimizing the growth of semiconductor materials by combining
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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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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
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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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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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magnetic resonance imaging (MRI), such as arterial spin labeling and diffusion tractography using programming scripts, such as Python and C++ Self-driven, motivated, and creative in designing image analysis
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future. Fueled by curiosity and a deep sense of duty, they contribute invaluable insights to research and teaching, enriching our society. Are you inspired and driven by the desire to make a meaningful