AstraZeneca is a major international healthcare business engaged in the research, development, manufacture and marketing of prescription pharmaceuticals and the supply of healthcare services. AstraZeneca is proud to offer a unique workplace culture that inspires innovation and collaboration. Co-workers are empowered to express diverse perspectives - and are made to feel valued, energized and rewarded for their ideas and creativity
Astrazeneca are seeking a bioinformatics scientist with a strong desire to apply computational biology tools to generate new hypothesis for Drug discovery safety efforts. The successful candidate must have experience with differential gene expression analysis and generation of biological hypothesis. Due to the diversity of the projects involved, the candidates with both basic and advanced skill sets in bioinformatics are encouraged to apply. The successful candidate will have an opportunity to train in new frontiers of computational biology and adjacent areas like machine learning/AI, providing support within the Data Sciences and Artificial Intelligence Department, in the Drug Safety and Metabolism (DSM) unit at AstraZeneca. He/She will partner with Drug Safety and Metabolism scientists and interact across the Innovative Medicine therapeutic area units for enabling research and development of pharmaceutical drugs.
Responsible for delivering computational biology support to project teams and/or to a business area. Coordinate work with, but operate with a high degree of independence and minimal supervision. Expected to flexibly cover a number of areas and projects as demand arises. Must have fundamental technical skills and good practical skills in the application of computational biology approaches to solve biological/scientific problems, with a focus on gene expression and pathway analysis to reveal causal gene-level molecular mechanisms of drug effects.
- A professional degree (Bachelor, MSc or PhD) in Computational Biology or related field (or equivalent qualification) with at least one year of dedicated research experience in gene expression analysis.
- Demonstrated experience in gene expression data analysis and hypothesis generation.
- Demonstrated expertise in at least one programming/scripting language (e.g., Perl, Python, R).
- Strong understanding of Biology
- Ability to grasp diverse computational biology concepts quickly
- Strong desire to learn new computational concepts
Deadline for applications: 2018-08-08. Selection is on-going and interviews will be held continuously which means the positions can be filled before deadline. Please make sure to send in your application at your earliest convenience!
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