Analyse and integrate multiple single-cell transcriptomics (scRNA-seq) datasets to identify pathways, signatures, and biomarkers which impact autoimmune diseases; Benchmark and validate computational methods and bioinformatics pipelines; Apply statistical and machine learning methods to characterize disease phenotypes and drug treatment effects; Contextualize and interpret statistical results to formulate hypothesis on mechanisms of disease; Visualize and present results of your work to an interdisciplinary audience
Requirements:
Master’s degree in bioinformatics, computational biology, or a related field; Excellent skills in data analysis, data visualization and statistical programming in R/Bioconductor; Good knowledge of computational, statistical methods for handling high dimensional ‘omics’ datasets. Prior experience in analysing scRNA-seq data is highly desirable
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März 2023 Switzerland Job Description 250! The number of genomics research projects that are waiting for your data analysis expertise every year. Your work will be important towards faster discovery and development of next generation breakthrough therapies for unmet medical need. The Immunology Disease Area at the Novartis Institutes for BioMedical Research (NIBR) in Basel is seeking a highly motivated postgraduate to join our Data Science team for an internship. Our team provides translational data science expertise and support to clinical and preclinical drug discovery programs targeting autoimmune diseases and chronic inflammation. We integrate and analyse internal and public biomedical data to enable strategies for patient stratification, compound differentiation, biomarker discovery, target identification and disease understanding. Timing: as soon as possible Duration: 6 month Your responsibilities: Analyse and integrate multiple single-cell transcriptomics (scRNA-seq) datasets to identify pathways, signatures, and biomarkers which impact autoimmune diseases Benchmark and validate computational methods and bioinformatics pipelines Apply statistical and machine learning methods to characterize disease phenotypes and drug treatment effects Contextualize and interpret statistical results to formulate hypothesis on mechanisms of disease Visualize and present results of your work to an interdisciplinary audience Diversity & Inclusion / EEO Novartis is committed to building an outstanding, inclusive work environment and diverse teams representative of the patients and communities we serve. Minimum Requirements What you’ll bring to the role: Master’s degree in bioinformatics, computational biology, or a related field Excellent skills in data analysis, data visualization and statistical programming in R/Bioconductor Good knowledge of computational, statistical methods for handling high dimensional ‘omics’ datasets. Prior experience in analysing scRNA-seq data is highly desirable Good understanding of biology and ability to contextualize results Ability to work independently and as part of an interdisciplinary team Excellent communication skills and knowledge of English. Why consider Novartis? 799 million lives were touched by Novartis medicines in 2020, and while we’re proud of this, we know there is so much more we could do to help improve and extend people’s lives. We believe new insights, perspectives and ground-breaking solutions can be found at the intersection of medical science and digital innovation. That a diverse, equitable and inclusive environment inspires new ways of working. We believe our potential can thrive and grow in an unbossed culture underpinned by integrity, curiosity and flexibility. And we can reinvent what's possible, when we collaborate with courage to aggressively and ambitiously tackle the world’s toughest medical challenges. Because the greatest risk in life, is the risk of never trying! Imagine what you could do here at Novartis! Division NIBR Business Unit IMMUNOLOGY - NIBR Location Switzerland Site Basel Company / Legal Entity Novartis Pharma AG Functional Area Interns/Students on Novartis Payroll Job Type Full Time Employment Type Internship Shift Work No
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