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The ideal applicant should have a strong programming background (e.g., Python, R, SQL, SAS, and/or STATA) and the drive and enthusiasm to learn about clinical care by assisting in state-of-the-art patient-centered research.
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Strong hands-on skills in relevant programming languages (e.g., R, Python, Shiny, UNIX/Linux, UNIX bash shell scripting, Nextflow), statistical software, cloud computing, visualization tools, and relevant R/Bioconductor packages.
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End-to-end implementation experience in building analytical solutions using data visualization tools like TIBCO Spotfire, Power BI, Python, R, etc. Collaborate with local business users to understand business processes, gather technical requirements, evaluate proof of concepts, design, develop, and support analytical solutions using TIBCO Spotfire, Power BI, SQL, Python, R, JS, HTML, etc.
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Expertise in Python, R, SQL, statistics, data mining. + Visualize insights using Microsoft Office, Tableau, Python, R. + Design, develop, and test ML applications using Python, Linux, Docker.
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Uses relevant programming languages (e.g., R, Python, Shiny, UNIX/Linux, UNIX bash shell scripting, Nextflow), statistical software, cloud computing, visualization tools, and relevant R/Bioconductor packages.
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Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Supervisory experience, Using open source frameworks (for example, scikit learn, tensorflow, torch.
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You will support R&D with single-cell and bulk RNA and DNA analysis and pipeline development while using and promoting best practices for coding (Python/R) and reproducible research.
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Use programming languages including but not limited to Python, R, SQL, Java or Scala, SQL. Programming Languages: Python, R, SQL, Java or Scala, SQL. Machine Learning and Deep Learning: Good understanding of: ML algorithms like linear regression, logistic regression, etc., supervised, unsupervised, and reinforcement learning, AI Frameworks like TensorFlow, PyTorch, scikit-learn etc., Neural network, NLP, computer vision, and predictive analytics.
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Hands-on software development solutions for R-Shiny, PowerBI, Tableau dashboard, Python, SQL development, with understanding of Javascript and Open Source GIS development frameworks. Development background and in depth experience with SQl, R-Shiny, Python languages PostgreSQL/PostGIS, SQL, MSSQL, Hadoop, or Oracle geodatabase design and data structures.
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Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch.
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Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch). Proficient in Python/R, PyTorch/TensorFlow, SQL, Big Data and cloud technologies.
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Data science, machine learning, optimization models, Master's degree in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch.
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Experience with any of the following technologies is a plus: Snowflake, Power BI, Microsoft SQL Server, Python, Power Shell, R/R Studio Workbench Server, Amazon AWS (EC2 instances, Redshift, lambda functions, S3, etc.
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You have strong skills in Python, R, SQL, and Hive queries. You have hands on experience with data visualization and reporting tools such as Tableau, R Shiny, and/or Looker. You have hands on experience with data visualization and reporting tools such as Tableau, R Shiny, and/or Looker.
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Experience with analytics tools like SAS, R, Python, and other advanced statistical software. Experience with at least one of the programming languages such as: JavaScript, Java, Python, or other.
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