Flow Cytometry – Bioinformatics – Senior Data Scientist Single Cell
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We seek an experienced computational biologist / data scientist to lead our single cell sequencing data analysis efforts for the Sanofi Research Flow Center of Excellence in Cambridge.
In this exciting role the Single Cell Data Analyst will advance our methods and application of single cell approaches for multiple Therapeutic Areas including Rare Disease, Immunology, Rare Blood disorders and Oncology.
In this hands-on role the Analyst will work as an integrated part of the Flow Cytometry Center of Excellence to design high content experiments, to manage data, and to use advanced analytical and computational techniques to build and to characterize a Human PBMC Biorepository as well as develop panels for Flow and Genomic Cytometry Approaches. Furthermore, the Analyst will collaborate with project teams across Research Therapeutic Areas to use the approaches to forward their project goals.
Summary of Key Responsibilities:
- Execute best practices for single cell methods including Imputation & Data Normalisation, Deconvolution, Cell Type/State Analysis, Cell to cell interaction / Trajectory inference, Reconstruction of Cell-type-Specific Interactomes, and spatial transcriptomic analysis and visualization
- Develop and advance computational methods and pipelines needed for current and future projects including TCR/BCR sequencing, neoantigen prediction, CITE/REAP-Seq
- Establish a platform for single cell data storage, access and visualization for the PBMC biorepository and other single cell datasets.
- Contribute to the design and refinement of multiplex antibody panels for CITE-seq and flow cytometry
- Ph.D. in a computational, statistical, biophysics, or bioinformatics related fields
- A minimum of 5-years research (academia or industry) experience
An ideal candidate will be collaborative, self-directed and possess
- First-hand experience in single cell sequencing analysis and methods as well as related computing infrastructure and data management methods .
- First-hand multi-parametric data mining experience on expression, copy number and profiling datasets for target identification and biomarker discovery. For example, multivariate analysis; dimensionality reduction methods; parametric and non-parametric statistical methods; Bayesian statistics; pattern recognition or classification methods.
- First-hand experience at integrating publicly or commercially available genetic, genomic, and interaction datasets with novel experimental data to identify testable hypotheses
- Statistical programming skills such as, Python, R/bioconductor or equivalents
- Prior experience analyzing multiplex flow cytometry data is a plus
Required Key Attributes
- Positive, proactive can-do mindset
- Demonstrated ability to lead projects of moderate scope, mapping-out critical path, milestones and timelines, as well as manage customer expectations with minimal supervision
- Developed communication and presentation skills and a successful track record of collaborating with cross-functional scientific teams
Sanofi Inc. and its U.S. affiliates are Equal Opportunity and Affirmative Action employers committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race; color; creed; religion; national origin; age; ancestry; nationality; marital, domestic partnership or civil union status; sex, gender, gender identity or expression; affectional or sexual orientation; disability; veteran or military status or liability for military status; domestic violence victim status; atypical cellular or blood trait; genetic information (including the refusal to submit to genetic testing) or any other characteristic protected by law.
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