Snabbfakta
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- Oxford
Ansök senast: 2024-06-12
Bioinformatician
We are working in partnership with a start-up biotech firm, supporting them in the growth of their business and they are seeking a Bioinformatician to join their team.
Role Summary
In this role you will be responsible for bioinformatic analysis of public and internal bulk and single cell RNA expression and T cell receptor datasets; bulk cell population datasets of protein expression and peptidome and SNP databases. (Desirable) You will use HLA-peptide prediction and machine learning algorithms. This effort will be crucial to identify potential peptide-HLA target antigens. You will use computational pipelines to study interactions between immune cells and tumour cells. You will support the discovery and validation of targets for soluble TCR therapeutics.
Full-time hybrid role, minimum of 2 days on-site per week (Oxford).
Key Deliverables
- Analyse public and proprietary datasets described above, covering both healthy, tumour and immune datasets;
- You will use the latest algorithms and pipelines, and develop your own tools, to interrogate the biological rationale of targets;
- Work closely with the biology team to support cutting-edge drug discovery and contribute to the production of a best-in-class computational ecosystem;
- Provide analytical and statistical rigour to empower better decision making in experimental design and development of therapeutics.
- Work collaboratively with the Biology and Protein Engineering teams to guide optimisation and development of soluble TCRs.
- Effectively design and conduct experimental work to align with Company priorities and meet scientific timelines, report results succinctly and effectively.
- Present scientific findings and summary conclusions to your department, project team and the company leadership team.
- Drive innovation and continuous improvement within the team, implementing novel technologies, workflows, and methodologies to enhance productivity and accelerate the drug development process
Experience & Qualifications Required
- Strong background in coding in R, Python and Pearl.
- Strong statistical background.
- Familiarity with machine learning algorithms.
- Track record of maintaining high code quality and documentation.
- Prior experience in the analysis of nucleic acid, protein databases both at a cell population and a single-cell level.
- Prior of peptidome databases.
- Prior experience of analysing HLA- peptide presentation algorithms.
- A PhD in relevant subject, ideally with subsequent biotechnology and/or pharmaceutical industry experience.
- Ability to be present locally, nationally and internationally.
- Working proactively with the team to develop effective strategies prioritised to the needs of the Company; collaborating effectively with other functions.
- Inclusive, collaborative, and thrives in a team environment with a flexible approach to working.
- Strong communication skills with the confidence and judgement to challenge appropriately.
- Demonstrable problem- solving ability, creative thinking and be pro-active in driving the project forwards;
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