Computational Biologist in Oncology (m/f/d)

Key Skills

Python Programming, Deep Learning, PyTorch, TensorFlow, R Programming, Molecular biology, Statistical modeling, Bioinformatics, Large scale deployment, Genomic data

Job Description

GSK is a science-led global healthcare company with a mission: we want to help people to do more, feel better, live longer. Our goal is to be one of the world’s most innovative, best performing and trusted healthcare companies. Our values and expectations are at the heart of everything we do and help define our culture - so that together we can deliver extraordinary things for our patients and consumers and make GSK a brilliant place to work. GSK offers excellent work-life balance for its employees and is an equal opportunity employer.

Our strategy to develop the next generation of transformative medicines relies on our investment in genetics, functional genomics, and data analytics.

Cellzome, the GSK site in Heidelberg, is located on the campus of the European Molecular Biology Laboratory (EMBL), a diverse and stimulating environment that provides a unique mixture of backgrounds and expertise. GSK and EMBL operate under a collaboration agreement enabling access to services and instrumentation at EMBL core facilities and are engaged in collaborations with research groups on campus.

Your Responsibilities:

We are seeking a motivated scientist in computational oncology to join our dynamic and expanding team. Your primary focus as a Computational Biologist (m/f/d) in the Oncology CB team would be to identify, develop, implement, and use computational biology methods for target identification, validation, and progression through the oncology drug discovery pipeline. Applicants should have strong analytical skills and a background in bioinformatics or computational biology, combined with knowledge of oncology.

You should be comfortable working in a dynamic and highly collaborative environment, and you will be expected to communicate complex informatics principles, methods, analyses, and results to scientists from diverse backgrounds. Furthermore, 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.

Why You?

Basic qualifications:

• PhD in Computational biology, bioinformatics, computational sciences, or biomedical/biological sciences.
• Experience in omics analysis for oncology applications
• Experience in a programming language (such as R, or Python) for complex data analysis.
• Knowledge of fundamental concepts in biology and statistics.
• Excellent communication skills and fluency in English

Preferred qualifications:

• Demonstrated experience in analysis of omics data either on a single cell or bulk level including contextualization of the results
• Skills to collect, integrate, mine and analyze complex biological data and translate these into testable hypotheses.
• Familiarity with common bioinformatics and oncology databases, resources, and tools.
• Familiarity with genome-wide genetic, genomic, pathway and network methods.