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field. Have proven expertise in statistical modelling and machine learning for large and complex datasets. Have proficiency in Python and/or R for time-series and sensor data analysis. Have an interest in
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Epidemiology, or a related field. Strong experience in statistical modelling, machine learning/deep learning, genomics and multimodal biological, and biobank data analysis. Proficiency in R, Python, Perl, and
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, XPS/AFM, electrical probing; DoE/statistics (Python/Matlab a plus). Strong documentation, safety discipline, and clear communication in English - essential for data analysis and communication with
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in at least one programming language (C/C++, Python, Java). Strong mentorship and communication skills for guiding students. Excellent interpersonal skills for effective collaboration with
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strictly required Familiarity with basic statistical or epidemiological concepts and data analysis Experience with R or Python for data wrangling and visualization Detail-oriented, organized, and able
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Maxwell’s equations and scientific programming (e.g., Matlab, Python, C++) Competent in teamwork and presenting results in informative visuals Interpersonal skill: Ability to work under pressure, Ability to
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) Excellent written, oral communication skills c) Prior programming experience (e.g., python, shell, JavaScript, Matlab) and familiarity with collaborative software development (e.g., git/github) is a plus d
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coding in bash and R/Python Experience in creating and maintaining Nextflow pipelines. Experiences of analyzing large-scale population data. Experiences working with electronic health records (desirable
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, economics, or a closely related field. Excellent knowledge of computational linguistic tools and machine learning techniques. Experience with data analysis with Python and STATA. Prior experience in
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• Proficiency in at least one statistical software (e.g., R, Stata, SPSS, Python) • Expertise in quantitative analysis, with preferred skills in o Quasi-experimental evaluation techniques (e.g., Difference-in