Team Leader, Computational Biology
Senior Principal Scientist
Onsite commutable from: New York, Connecticut, New Jersey
Up to 80% remote
Are you an outstanding computational biologist who has brilliant leadership experience?
You could join a rapidly growing, global pharmaceutical company's Cardiometabolic Diseases Research department as a highly motivated and exceptional skilled Senior Principal Computational Biologist (Team Lead) . In your new role, you will lead the strategy and implementation of data and analytics-driven drug discovery approaches for the department. Your new role will bring together the scientific questions faced by Cardiometabolic Diseases Research with bioinformatics capabilities, both internally and externally, to expand the understanding of disease biology and bring novel therapies to patients, with a particular emphasis on NASH.
As a Senior Principal Computational Biologist, will lead a small, on-site team of computational biologists, while also interacting with CMDR leadership to align with department's strategy. You will also coordinate with Computational Biology, IT, and other department experts globally to ensure CMDR bioinformatics needs are met.
* Ph.D. in Bioinformatics or Biology, Chemistry or Biostatistics with a postdoc in Bioinformatics.
* 7 + years of relevant experience in drug discovery or biomedical research environment after completing a doctoral degree.
* Proven track record of designing, leading, and managing complex computational research projects.
* Expert in bioinformatics tools and methods and high-level expertise in multi-modal omics data integration, single cell omics, GWAS, and machine learning/deep learning.
* Proficiency using R and Python.
* Familiarity with Agile development methodologies
401K Match, 20% Bonus, Medical Insurance, Relocation support and Generous PTO
Please feel free to contact Jade Page for a confidential discussion about this role at email@example.com, or apply to this advert and send along your CV. We look forward to hearing from you!
Keywords: Computational Biology, Bioinformatics, Immunology, Translational Bioinformatics, R, Python, GWAS, Machine Learning, NASH, Drug Discovery, Diabetes, Obesity, Metabolic Diseases