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research focuses on how RNA biology influences cell fate decisions, during either epithelial-to-mesenchymal transition (EMT) in cancer, or during early neural development. Our recent work reveals that coding
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assessments. Data management and analysis. Appropriately code and de-identify data in an organized, systematic way and save data to appropriate servers and/or databases. Perform data cleaning and pre-processing
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sensor integration. Strong coding and debugging skills. Excellent communication, documentation capabilities and a demonstrated track record of publication. An enthusiasm for developing new measurements
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superb quantitative background, strong coding skills (e.g., Python, R), expertise in infectious disease modeling across multiple pathogens, expertise with large datasets and statistical analysis, and high
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accomplishments, (b) Your broader research interests, and (c) why you are interested in working with us A sample of data analysis code (published or unpublished) A representative writing sample (published
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and other machine learning models (especially neural network models, time-series models) and coding in python and R. Strong collaborative skills and ability to work well in a complex, multidisciplinary
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applying data science principles and techniques to biomedical datasets. Applicants should be comfortable using coding skills such as SQL, R, and Python to extract data from databases, clean it, and analyze
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with electronic health record (EHR) and/or clinical data. Proficiency in Python, with strong coding and debugging skills. Experience with deep learning frameworks such as PyTorch, JAX, TensorFlow
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latent variable models (especially factor analysis, item response theory, and growth modeling) and coding in R. Strong collaborative skills and ability to work well in a complex, multidisciplinary
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response theory, and growth modeling) and coding in R. Strong collaborative skills and ability to work well in a complex, multidisciplinary environment across multiple teams, with the ability to prioritize