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systems, with emphasis on criteria for robustness, reliability, and stability. Topics of interest include the study of symmetries and equivariance and their implementation in deep neural networks
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, transferring and transforming data, and statistical data analysis. Experience in using one or more statistical software packages (e.g. R or similar). Experience working with routinely collected cardiovascular
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annotation of these metabolomes using multistage fragmentation (MSⁿ) data, incorporating novel computational methods and strategies (e.g. spectral matching, network-based approaches, machine learning) where
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units in neural networks, which drive both artificial and natural intelligence. Current projects span a wide range of topics in deep learning theory and theoretical neuroscience. For more information and
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works to interpret genomes and distill the immensely complex networks that form the foundation of human biology and disease, through accurate machine learning models. Current areas of interest include
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and engineers) in the other CoSTAR Labs, and similar labs around the UK outside the CoSTAR Network. About the Role As our second CoSTAR Foresight Lab Research Fellow at Goldsmiths, you will play a key
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place to define your career. The University is located within a beautiful historic city, home to a UNESCO World Heritage Site, and surrounded by stunning countryside. Our talented scholars and researchers
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encouraged to mentor junior trainees in the lab. Essential Functions Conduct research experiments within the defined scope of the lab?s scientific focus. Analyze experimental and omics data, develop and test
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to writing of journal articles and conference presentations Operate within area of specialism and collaborate with a wider interdisciplinary research team Participate in wider networks, including the Adult
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the research projects - “A digital twin for enhancing coastal resilience against extreme storm surges in Hong Kong” and/or “Hong Kong coastal HF-radar network”. Qualifications Applicants for the Research Fellow