Job Reference: J5632132
Updated On: 23/10/2019
Status: Now Interviewing
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Role OverviewWe are currently looking for a Computational Biologist to join a leading biotechnology company based in the London area. As the Computational Biologist you will be responsible for informatics support that contributes towards building a machine learning platform for the discovery of antibody and protein therapeutics.
Key Duties and ResponsibilitiesYour duties as the Computational Biologist will be varied however the key duties and responsibilities are as follows:
1. As a Computational Biologist you will analysing NGS and amplicon-based data derived from the laboratory team, followed by interpretation to draw significant conclusions with the research and development team.
2. Whilst collaborating with the automation and data scientists you will develop pipelines that can analyse barcode/ UMI containing libraries.
3. You will design synthetic antibody fragment libraries and analyse protein sequence data sets to product mapping fitness landscapes and sequence alignments.
4. You will collaborate with wet-lab scientists in order to plan and continously improve experiements with regards to data quality.
To be successful in your application to this exciting opportunity as the Computational Biologist we are looking to identify the following on your profile and past history:
1. Relevant PhD in Bioinformatics, Molecular Biology or another related scientific discipline.
2. Proven industry experience in developing custom pipelines for analysis of NGS data from variant libraries. Experience analysing protein sequncing data will be desirable for the role.
3. A working knowledge of applied statistics, bioinformatics tools and databases and strong practical experience programming in Python. Experience using molecular modelling software such as Pymol is desirable.
Key Words: Bioinformatician, Bioinformatics, Analysis, Programming, Pipeline, NGS, Amplicon, Python, Statistics, Library, Protein, Antibody, Therapeutics, Data, Design, Biotechnology, Machine Learning, Artificial Intelligence
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