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, metabolomics, and host immune profiling. This position is designed for a candidate interested in leading analytical efforts and developing manuscripts, while working closely with a multidisciplinary team
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. Her team is investigating biological processes that are critical to the progression of cancer and other diseases by using quantitative super-resolution microscopy. For more information on the Jovanovic
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Are you passionate about using geospatial data and place-based analytics to address mental health inequalities in rural and coastal communities? The University of Lincoln is seeking an ambitious
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | about 1 month ago
/Administrative Internal Number: 25565 POSTDOCTORAL ASSOCIATE, McGovern Institute for Brain Research and Department of Brain and Cognitive Sciences, to develop computational circuit models, analytical theory, and
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apply analytical workflows for high-throughput breath analysis, ensuring robust and reproducible data. Work closely with clinical and research partners to translate findings into practical screening
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3 Apr 2026 Job Information Organisation/Company Leiden University Research Field Chemistry » Analytical chemistry Chemistry » Instrumental analysis Engineering » Biomedical engineering Engineering
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and real-time analytics. Develop and apply non-destructive testing (NDT) methods and data-driven approaches to determine material properties of reclaimed steel. Investigate geometric imperfections
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evidence. Six case study landscapes across Ireland form the core analytical framework, each illuminating different demographic, environmental, social, and religious impacts of the Famine. The successful
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a relevant field and have strong quantitative and analytical skills, including experience in food systems modelling or closely related areas. Proficiency in data analysis and coding (e.g. Python, R
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The Role The role focuses on advancing research in explainable and trustworthy machine learning, with a particular emphasis on mechanistic interpretability and its application to healthcare data