In this role you work on the analysis, integration, and interpretation of multiple types of omics data collected as part of our clinical trials in dermatology and rheumatology. You will be responsible for: - Application of modern biostatistics and machine learning methods to high-throughput molecular and clinical data - Analysis, integration and visualization of different types of omics data, including genomics, transcriptomics and proteomics - Contextualization of results from omics experiments, including correlation with clinical endpoints and phenotypes, generation and comparison of molecular signatures, pathway- and network- level analyses - Communicating with and presenting your work to a diverse audience of biologists, clinicians and data scientists
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Global Pharma Company.
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- Excellent knowledge of computational methods for the analysis, integration and interpretation of multiple types of high-throughput biological data from sequencing and/or array-based technologies. Experience with the analysis of single-cell genomics data is considered a plus - Demonstrated experience with the application of supervised and unsupervised machine learning methods to biomedical data - Excellent skills in data analysis, data visualization and statistical programming in R/Bioconductor - Familiarity with Linux/Unix command line and high-performance computing environments
PhD in bioinformatics, computational biology, biostatistics, data science, biomedical informatics or a related field
English : Very good