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in algorithms development and refinement; (b) a good command of both written and spoken English; and (c) at least two first-authored publications. Preference will be given to those with: (a
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, inferential, and multivariate methods, including principal component analysis (PCA), regression, and machine learning algorithms (e.g., Random Forest), with the aim of integrating various environmental exposure
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Medicine and Bioinformatics. The specific objectives of the project are to (i) deploy network analysis methods to genomic data (50%), and (ii) develop such algorithms including community detection algorithms
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. There are opportunities to broaden out into other areas such as new algorithm development, and advanced computational methodologies for integrated analyses. You will have a key role in planning, designing and executing a
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We are seeking an outstanding, creative researcher with the skills to develop novel, ‘artificially intelligent’ approaches to the application of nanofabrication techniques – see, for example https
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with major in Power Engineering • Relevant experience in power electronics, drives, control algorithms, optimization techniques, and optimal energy management algorithm development for the optimal
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based at the School of Electronics and Computer Science, Southampton. The project is researching, developing and evaluating decentralised algorithms, meta-information data structures and indexing
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(IMI, IMT, IRS, Census) with descriptive methods and causal econometric techniques. It will use various approaches to identify vacant dwellings, including machine learning algorithms to visually detect
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working collaboratively to lead the world to better health. Here, you will thrive in an innovative and inclusive atmosphere and your personal development and wellbeing will be supported. We invite you to
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Responsibilities: Conduct programming and software development for data management. Design and implement machine learning models for optimizing data management. Conduct experiments and evaluations of the designed