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Field
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Associate will contribute to ongoing projects and have the opportunity to develop independent research aligned with the aims of the ADN lab. Current work focuses on machine learning and multivariate decoding
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computational methods to develop critical medicines for improving global health and equality. For low-income populations in developing countries, access to life-saving medicines is often fraught with obstacles
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objects or systems, experience developing and running codes for simulating astrophysical nuclear reactions and in evaluation of thermonuclear reaction rates, experience working with graduate and
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excimer lasers for laser inertial fusion energy. Conferences, Publications, etc.: Write scientific papers, participate in conferences, prepare PowerPoint presentations/slides, make calculations, and
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accounting, and database maintenance. They will also participate in an average of one research cruise per year. It is anticipated that the Research Assistant Professor will develop their own independent
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collaboration tools, such as Google Meet. Help design future research challenges through the preparation and publication of data, software, and web-based documentation (eg Google Docs). Collaborate and
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modeling and simulation tools DESIRED QUALIFICATIONS: Experience using NONMEM, R, Monolix and/or other platforms for analysis of clinical and/or preclinical pharmacology data; development of web-based tools
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-development of a web-based platform to personalise domiciliary care for people with dementia Assist in the delivery of other study work packages and potentially other dementia-focused projects Contribute
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development staff. They will also need to work effectively with partners and members of the public/service users to develop, deliver and disseminate the work of the research programme. Situated within one
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collaboration tools, such as Google Meet. Help design future research challenges through the preparation and publication of data, software, and web-based documentation (eg Google Docs). Collaborate and