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JW, Surov SS, Liang Y, Parunov LA, Ovanesov MV. Effect of pH on thrombin activity measured by calibrated automated thrombinography. Res Pract Thromb Haemost. 2020 Jun 12;4(5):944-945. Learning
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expression, cell state-specific regulatory programs, and clinical outcomes. Related projects will include: Develop and apply statistical or machine learning approaches to model the effects of common and rare
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discipline* Good knowledge and experience in at least one of the following: cancer biology / cancer immunology / epithelial cell biology / evolutionary biology / genomics / statistics / mathematics or machine
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reconfigurable RF hardware for CAP-MIMO systems and contributing to machine learning-enhanced ISAC methods development through EM-informed modelling and hardware design. This is a unique opportunity to build
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Is the Job related to staff position within a Research Infrastructure? No Offer Description You are keen on contributing to new advances in deep learning methodology for imaging for monitoring marine
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automation, computational drug design, machine learning, and software engineering. The ideal candidate will contribute to innovative research and the development of advanced computational tools within our lab
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years with research duties exclusively,. A career plan will be prepared that specifies the competencies that the Research Fellow will acquire. Access to career guidance will be provided throughout
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Technologies (CQT) The Centre for Quantum Technologies (CQT) in Singapore brings together physicists, computer scientists and engineers to do basic research on quantum physics and to build devices based
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coarse grained reconfigurable arrays (CGRAs), virtualisation of FPGAs using partial reconfiguration, and accelerator support for machine learning. Postdocs at KAUST enjoy generous salaries and free
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, glioblastomas, colon cancer, and lung cancer. Advancing precision oncology through machine-learning models: We integrate multimodal patient data, including multiomic data and health record information, to develop