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the application process may be addressed to jobs@lshtm.ac.uk . Please quote reference EPH-EPED-2025-14. The supporting statement section should set out how your qualifications, experience and training meet each
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themes are not covered, including conventional medical imaging). Examples include Bayesian optimization for molecular or materials design; machine learning for single cell data; physics-based ML
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themes are not covered, including conventional medical imaging). Examples include Bayesian optimization for molecular or materials design; machine learning for single cell data; physics-based ML
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, including conventional medical imaging). Examples include Bayesian optimization for molecular or materials design; machine learning for single cell data; physics-based ML for turbine design and
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, including conventional medical imaging). Examples include Bayesian optimization for molecular or materials design; machine learning for single cell data; physics-based ML for turbine design and
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systems for diagnosis and assessment of infant brain pathology. The job will involve designing, building, and evaluating a new kind of optical imaging system for assessing a variety of newborn infant in a
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conferences. If you have are excited about Computational Fluid-Structure Interaction and have the relevant skills and expertise to make a positive impact on our project, then we would love to hear from you
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employment initiatives for people who experience complex barriers to employment’. This project will build a partnership to help us understand how to support people who experience complex barriers to employment
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capture, emphasis on skill-building – we talk about building technology to help people get off technology. Our lab operates within the School of Electronics and Computer Science, with strong
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-depth characterisation and annotation of these metabolomes using multistage fragmentation (MSⁿ) data, incorporating novel computational methods and strategies (e.g. spectral matching, network-based