Computational Biologist/Principal Scientist, Applied & Translational Omics (m/f/d)

Role Summary

Computational Biologist/Principal Scientist, Applied & Translational Omics (m/f/d). The role focuses on evaluation and application of novel methods for the analysis and integration of spatial and single-cell data to impact the GSK pipeline. It involves working in a multidisciplinary, collaborative environment across disease areas to advance drug discovery and clinical development. Locations include Heidelberg Office; Cambridge (MA); Stevenage (UK); Upper Providence (PA); Boston South (MA).

Responsibilities

• Impact the GSK drug development pipeline through development, evaluation and application of innovative computational and statistical approaches to the analysis and interpretation of spatial and single cell data.
• Contribute to the evaluation and development of best practice methods for spatial and single cell omics and to the upskilling of others.
• Work within cross-functional project teams with GSK scientists and external collaborators, with an emphasis on respiratory, immunology, neurodegeneration or metabolic disease.
• Effectively communicate analysis findings, with expert interpretation, to project teams.
• Work with focus and agility to deliver against objectives, demonstrating strong statistical, analytic and critical thinking skills.

Qualifications

• Extensive experience in the analysis of single-cell and spatial omics datasets, with proven ability to derive and apply novel insights from these and other emerging genomic technologies.
• Familiarity with, and ability to critically evaluate, the development of cutting-edge tools and frameworks for single-cell and spatial data integration, visualization, and interpretation.
• Strong proficiency in at least one of R and/or Python, with a track record of writing reproducible and scalable code.
• Proven expertise in statistical modelling, hypothesis testing, and data-driven inference.
• Data science skills to collect, integrate, mine, analyse and interpret complex diverse biological data and translate them into testable hypotheses.
• Ability to understand key scientific questions and identify and develop innovative computational solutions to answer them and impact the drug discovery pipeline.
• Demonstrated experience in effectively communicating complex scientific concepts to diverse audiences.
• Demonstrated ability to work effectively multidisciplinary teams.
• PhD or equivalent experience in a relevant scientific discipline (e.g. computational biology, biomedical/biological sciences, biomedical statistics, computational sciences, bioinformatics or machine learning) with a history of impactful scientific publications and/or presentations.

Skills

• Computational biology and data science: spatial and single-cell omics data analysis, data integration, visualization, and interpretation.
• Programming: R and/or Python with reproducible, scalable code development.
• Statistical modelling, hypothesis testing and data-driven inference.
• Scientific communication and collaboration in multidisciplinary teams.

Education

• PhD or equivalent experience in a relevant scientific discipline (e.g., computational biology, biomedical/biological sciences, biomedical statistics, computational sciences, bioinformatics or machine learning) with a record of impactful publications and/or presentations.