Our Purpose
At GSK, we have bold ambitions for patients, aiming to positively impact the health of 2.5 billion people by the end of the decade. Our R&D focuses on discovering and delivering vaccines and medicines, combining our understanding of the immune system with cutting-edge technology to transform people's lives. GSK fosters a culture ambitious for patients, accountable for impact, and committed to doing the right thing, making sure that we focus our efforts on accelerating significant assets that meet patients' needs and have the highest probability of success. We're uniting science, technology, and talent to get ahead of disease together.

Location: Hertfordshire - Stevenage

Principal Scientist (m/f/d) Genomic Technologies, Human Genetics and Genomics
This position may be based at a GSK R&D site in UK (Stevenage), in USA (Cambridge Tech Square, MA; or Upper Providence, PA), or in Germany (Heidelberg).

We are seeking an innovative scientist to join our team. The successful candidate will join the Genomic Technologies team, within GSK R&D Translational Sciences. In the Genomic Technologies group, we integrate deep and broad expertise in computational and statistical methods and techniques, to enable best-in-class analytical insight and interpretation of genetics and genomics data, to guide GSK's drug discovery and development portfolio and pipeline decisions.

The successful candidate will join an existing Statistical Genetics team and will work on projects aligned to current areas of focus, including:

• Discovery of new causal gene-phenotype links through analysis of large-scale individual level human genetic data.
• Identification of causal genes, disease-relevant mechanisms and cell types, potential drug targets, candidate biomarkers, patient subgroups and disease subtypes, through integration of genetic association data across multiple 'omic and phenotypic layers.
• Predictive modelling of presence, direction and magnitude of causal gene-phenotype links, using genetic and 'omic data, mechanistic annotation, inferred causal networks, and genome-scale perturbation data.

We encourage applicants to describe in their cover letter how their qualifications, skills and experience would make them outstanding contributors to the work of Genomic Technologies and of HGG.

Responsibilities

• Evaluating, improving, testing, and developing production implementations of best-in-class methods for analysis of genetic data, in collaboration with scientists in Data and Predictive Sciences, Biostatistics, or/and AI/ML teams.
• Generating large-scale analysis outputs, and/or implementing state-of-the-art tools for dynamically analysing, interpreting, and visualizing genetic and genomic data.
• Collaborating with partners in applied and translational teams across HGG, in experimental Target Discovery, and in GSK disease area Research Units, to influence portfolio and pipeline decisions.
• Staying informed about recent research in the field and considering its potential for application within GSK.
• Contributing to a culture of innovation, quality, and willingness to learn and improve.

Why you?
Qualifications, Skills and Experience:

• Advanced degree (PhD or equivalent) in a relevant scientific discipline.
• Experience working with large scale biobank data, such as UK Biobank and All of Us.
• Excellent programming skills in R or python, and application of techniques in reproducible research, literate programming, FAIR data principles, or software development.
• Experience of evaluating, improving, testing, and/or developing methods for analysis and interpretation of large-scale genetics data.
• Strong communication and team-working skills.

Preferred Skills & Experience:

• Deep understanding of statistical genetics methodology.
• Experience working in cloud-based Trusted Research Environments.
• Experience with machine learning and/or advanced statistical methods.
• Experience working in multidisciplinary teams on complex and impactful projects.
• Experience with analysis of very large datasets using distributed or cloud computing technologies (e.g. SQL, PySpark, BigQuery, Docker, Nextflow).

#LI-GSK

Skills
Applied Statistics, Data Analysis, Data Engineering, Data Science, Datasets, Drug Development, Drug Discovery Process, Drug Target Identification, Genetic Analysis, Genomic Analysis, Machine Learning (ML), Software Engineering

Germany Salary Range: EUR 74,250 to EUR 123,750 and US salary ranges are shown in the source advert for other locations; no UK salary range is published for this role.

Why GSK?
Uniting science, technology and talent to get ahead of disease together.

GSK is a global biopharma company with a purpose to unite science, technology and talent to get ahead of disease together. We aim to positively impact the health of 2.5 billion people by the end of the decade, as a successful, growing company where people can thrive. We get ahead of disease by preventing and treating it with innovation in specialty medicines and vaccines. We focus on four therapeutic areas: respiratory, immunology and inflammation; oncology; HIV; and infectious diseases – to impact health at scale.

People and patients around the world count on the medicines and vaccines we make, so we're committed to creating an environment where our people can thrive and focus on what matters most. Our culture of being ambitious for patients, accountable for impact and doing the right thing is the foundation for how, together, we deliver for patients, shareholders and our people.

Should you require any adjustments to our process to assist you in demonstrating your strengths and capabilities contact us at DE.Contact-Recruitment@gsk.com where you can also request a call.

Please note should your inquiry not relate to adjustments, we will not be able to support you through these channels. However, we have created a Recruitment FAQ guide. Click the link where you will find answers to multiple questions we receive.

GSK is an Equal Opportunity Employer. This ensures that all qualified applicants will receive equal consideration for employment without regard to ethnicity, colour, religion, sex (including pregnancy, gender identity, and sexual orientation), parental status, national origin, age, disability, genetic information (including family medical history), military service or any basis prohibited under federal, state or local law.

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