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Senior Bioinformatician
3 months ago
Job Title: Senior Bioinformatician
Location: London, UK
About Us:
Our client are a pioneering biotechnology company dedicated to advancing research and developing various solid tumour programs. We are committed to improving the lives of patients worldwide by harnessing the power of science and medicine. As we continue to expand our portfolio of ground-breaking therapies, we are seeking a highly motivated and experienced Senior Bioinformatician.
Key Responsibilities:
- Partner with scientists and external collaborators to help design experiments, draft and implement analysis plans, and iteratively deliver actionable biological insights and visualizations
- Refine key questions, clearly articulate concepts, needs, and potential solutions, and effectively communicate results to diverse teams
- Establish, test, and improve analysis pipelines, especially for proteomics data
- Identify, ingest, validate, and harmonize key data resources to expand upon and translate insights broadly across modalities, models, and cohorts
- Develop innovative analytical approaches and analysis plans integrating, analysing, and interpreting high-dimensional multimodal datasets to provide evidence to progress the company portfolio
- Ensure data and analytics integrity through best practices in FAIR data, reproducibility, and documentation
Qualifications:
- Ph.D. in Bioinformatics, Computational Biology, Biostatistics, or related field with 3+ years of post-degree experience
- Strong programming/scripting skills in R and/or Python, as well as experience working with cloud services (e.g., AWS) and workflow languages (e.g., NextFlow)
- Expertise in quantitative proteomics, including familiarity with mass spectrometry technologies (e.g., LFQ and TMT), hands-on experience with analysis pipelines, and use of key public data resources (e.g., UniProt, STRING).
- Strong hands-on experience of performing analyses in at least one of:-
- Bulk and/or scRNAseq
- Molecular imaging, including spatial proteomics and/or transcriptomics
- Multi-omics and data integration
- Strong foundation in statistics and/or machine learning, including experience with methods such as survival analysis, regression analysis, dimensionality reduction, classification, and clustering
