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Field
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transition analysis to understand the actors, relationships, interdependencies, barriers and enabling conditions influencing technology deployment and scale-up. Design and undertake mixed-methods research
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innovative statistical methods. The main focus will be on methods for sample size estimation and reliability for functional data. More applied projects aimed at improving the understanding of movement data may
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grant proposal writing, and related tasks. Further development and practical implementation of innovative MRI acquisition and data analysis methods. Providing scientific and methodological support and
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. Teamwork: Ability to work collaboratively with others and contribute to a team environment. Technical Proficiency: Skilled in using office software, technology, and relevant computer applications
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software, technology, and relevant computer applications. Communication: Strong and clear written and verbal communication skills for interacting with colleagues and stakeholders. This is a core job profile
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the dissertation, must be completed by the date of appointment. Demonstrated research experience with density functional theory or closely related first-principles atomistic simulation methods. Demonstrated research
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-time, and evidence-accumulation phenomena. Implement simulation, parameter-estimation, and model-comparison methods in Python, MATLAB, R, or related computational environments. Lead and co-author
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be shown. Preferred Qualifications: ● Experience analyzing genomic and/or metagenomic data using computational methods. ● Experience developing new approaches for the analysis of biological
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Jersey. This project integrates residential histories, geospatial air-pollution estimates, cancer registry data, medical and pharmacy records, patient-reported outcomes, and circulating biomarkers
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and adapt assimilation schemes based on generative deep learning methods (such as flow matching and diffusion models). The candidate should have previous experience in data assimilation and/or deep