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What you'll need:
As well as strong communication, organizational, and time management skills, you will have:
Senior Proteomics Bioinformatician
- Posted 18 July 2024
- LocationLondon
- Job type Permanent
- Reference200974
- Contact NameYasin Ahmad
Job description
- 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, analyzing, and interpreting high-dimensional multimodal datasets to provide evidence to progress the Engitix portfolio
- Ensure data and analytics integrity through best practices in FAIR data, reproducibility, and documentation
What you'll need:
As well as strong communication, organizational, and time management skills, you will have:
- 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