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proficiency in R and/or Python for statistical modeling and large-scale data analysis; experience developing reproducible computational workflows is preferred Experience with Linux-based environments and large
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controlled trials (RCTs) in developing countries. Candidates should have strong quantitative skills, including proficiency in statistical software (e.g. Stata, R, or Python). Experience coordinating field
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, with the ability to translate complex data into actionable insights. Proficiency in data analysis tools and programming languages (e.g., SQL, Python, R) for data manipulation, analysis, and visualization
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Python, NCL, and MATLAB. Should have proficiency in scientific computing, high-performance computing (HPC), and scripting (e.g., Bash, CDO/NCO). Should have strong quantitative and analytical skills in
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• Computational skills for multi-omic data analysis (R, Python) is a plus. Department Contact for Questions Dr. Asmaa El-Kenawi Email: asmaa.elkenawi@cancerimmunometabolism.com Website: https
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with computational environments for ’omics data manipulation (command line, Python, R, etc.) * Deep knowledge in at least one relevant subdiscipline, i.e. bioinformatics, microbiology, microbial ecology
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for analysis (e.g., text manipulation); One or more computational environments for statistical analysis (e.g., MATLAB, Stata, R, or Python); Creating and managing very large datasets; Managing and mentoring
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. Basic Qualifications An ideal candidate will have a PhD in computational biology/bioinformatics/statistics/CS or another quantitative field, as well as superb programming (Python, shell scripting) and
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. Strong fundamentals in cancer biology and statistics are essential. Demonstrated proficiency in multiple programming languages such as Python/R, with experience in computational analysis of omics datasets
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interventions. Candidates need to be able to understand statistical modelling, have a mathematical background, and be fluent in R programming. We will also consider candidates who have extensive C++ or Python