We are seeking motivated, innovative and skilled computational biologists to join our expanding team within the Human Genetics department. Candidates should be keen to drive and apply state of the art analysis methods to inform decision making across the GSK pipeline, integrating diverse and complex data types to translate genetic signals into innovative new medicines for patients with unmet medical need. You will be encouraged to develop and advance your computational biology skills as well as your internal and external scientific profile through presentations and peer-reviewed publications.
GSK aims to improve the number of successful late stage clinical trials for innovative medicines, by both identifying and advancing drug targets that have strong evidence of a causal role in disease biology. The Human Genetics team leverages major scientific and technological advances, including investment in biobanks linked to large-scale human health databases, cutting-edge informatics platforms, breakthrough understanding of biological pathways, functional genomics capabilities built upon rapid progress in gene editing, and leading industry-academia partnerships, in order to identify and progress the best targets through the GSK pipeline.
Successful candidates will:
Help progress the GSK pipeline: Apply innovative computational approaches to translate human genetic and genomic evidence to drive decisions on target selection, validation and clinical translation.
Work in teams: Lead and participate in cross-functional project teams with GSK scientists and external collaborators.
Communicate: Be responsible for effective communication of analysis findings, with expert interpretation, to project teams.
Multiple Locations: Collegeville, Pennsylvania; Cambridge, Massachusetts.
We are looking for professionals with these required skills to achieve our goals:
PhD or equivalent experience in computational biology, bioinformatics, genetics, computational sciences, machine learning or biomedical/biological sciences.
Experience in a programming language (such as R, Python or Perl) for complex data analysis.
Experience leading and working within collaborative, multidisciplinary teams.
If you have the following characteristics, it would be a plus
Experience in the analysis of multi-omics data (e.g. transcriptomics, regulatory genomics, proteomics), including at the single cell level
Knowledge of genome-wide genetic, genomic, pathway and network methods
Skills to collect, integrate, mine and analyse complex biological data and translate them into testable hypotheses
Experience in analysing data sets related to immunology, neuroscience or infectious disease
Knowledge of the drug discovery and development process.
Publication record in peer reviewed journals.