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. Required competencies: Strong background in bioinformatics (e.g., R, Linux, Python). Experience working with large cohorts and high-dimensional data. Experience with microbiome analysis and/or GWAS
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learning, or a related field Strong background in deep learning and statistical analysis Proficiency in Python, R, and deep learning frameworks (e.g. PyTorch, TensorFlow) Strong written and verbal
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also being a mentor to other members of the community. KNOWLEDGE, SKILLS, AND ABILITIES REQUIRED: Background in machine learning Background in cancer biology Experience with R and/or Python Experience
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to process tissue data reproducibly and at scale Conduct analyses using programming languages such as R and Python Collaborate with other laboratory members with expertise in epidemiology, bioinformatics
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Computer Science, Biomedical Engineering, Statistics, Biomedical Sciences, Electrical Engineering, or a related quantitative field Strong programming skills (e.g., Python, R, or similar) Demonstrated research
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technologies, is highly desirable. Skills: Strong knowledge of clinical informatics frameworks, standards, and methodologies. Proficiency in data analysis software (e.g., R, Python, SAS, SPSS, SQL) and
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technologies, is highly desirable. Skills: Strong knowledge of clinical informatics frameworks, standards, and methodologies. Proficiency in data analysis software (e.g., R, Python, SAS, SPSS, SQL) and