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and excellent training and development opportunities. For further information about the post, please see the how to apply document, job description and the person specification. If you have any
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with an inspiring and diversified research environment that offers invaluable opportunities to encounter and exchange ideas and information with other up-and-coming colleagues from different disciplines
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research strategic development and securing funding Support research data management and documentation Job Requirements: PhD degree in Mechanical/Electrical Engineering or related field At least 1 years of
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at the intersection of numerical analysis, uncertainty quantification, and scientific machine learning. The research will primarily focus on probabilistic methods for data-driven model reduction, with
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novel methods and statistical software that are tailor-made to the research questions and data of CREATE. The successful candidate will conduct advanced methodological and psychometric research. Potential
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expected to take the lead role in their projects, publish manuscripts as the first author, and present their projects and data at lab meetings, as well as international meetings. We are looking for someone
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Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | 2 days ago
miscategorization of subjects with potential DILI risk during regulatory review. Through this opportunity, you will cooperate in research and training activities related to computer modeling and statistical analyses
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application consists of: An application Transcripts – Click here for detailed information about acceptable transcripts A current resume/CV, including academic history, employment history, relevant experiences
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application consists of: An application Transcripts – Click here for detailed information about acceptable transcripts A current resume/CV, including academic history, employment history, relevant experiences
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Information Mark Peterson Contact Email mpeterson@seas.harvard.edu Salary Range $67,600 – $91,826 Pay offered to the selected candidate is dependent on factors such as rank, years of experience, training