Clinical Scientist; Bioinformatician
UK
Listed on 2026-03-12
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Healthcare
Data Scientist, Medical Science, Clinical Research
Job Summary
Clinical Scientist in Bioinformatics (Band
7) – Bristol Genetics Laboratory, South West Genomics Laboratory Hub
We are seeking a Clinical Scientist (Bioinformatics) to join our Bioinformatics Team and support our state‑of‑the‑art diagnostic laboratory in delivering comprehensive genetic testing services to patients.
What we offer- A chance to be at the forefront of precision medicine, contributing to life‑changing diagnoses and therapies
- An environment that values innovation, collaboration, and professional growth
- Opportunities to work with diverse technologies and methodologies
- Supportive of flexible working and open to working from home options
This dynamic role involves operating in‑service bioinformatics pipelines and developing new bioinformatics services.
In‑service duties include running NGS pipelines for Rare Disease and Cancer services, performing quality control checks, and supporting scientific queries.
The post holder collaborates with the SWGLH bioinformatics team to develop and validate new pipelines for the NHSE National Genomics Test Directory.
Additional responsibilities include contributing to staff training, participating in quality assurance activities, and working with staff across the laboratory.
The post is open to HCPC registered Clinical Scientists in Bioinformatics. Applications from final‑year Scientist Training Programme (STP) trainees are welcomed.
The role requires specialist knowledge, analytical thinking, and collaborative skills. Experience in a diagnostic genetics laboratory’s bioinformatics section, and knowledge of bioinformatics tools, resources and techniques applied to medical genetics, are essential.
Candidates not yet registered will be expected to work toward HCPC registration and will be appointed at a salary band appropriate to their experience.
Successful candidates will work 37½ hours per week full‑time over seven days a week. Part‑time and job‑share options are considered.
Job Responsibilities- Data Analysis & Interpretation
:
Conduct comprehensive analysis of genomic data using bioinformatics tools and methodologies; interpret results in the context of rare diseases and cancer to support clinical decisions. - Pipeline Development & Management
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Develop, validate, and maintain bioinformatics pipelines for high‑throughput genetic data processing; ensure accuracy and efficiency of data analysis. - Service Development
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Actively participate in creating and enhancing new genetic testing services; stay abreast of bioinformatics advancements to drive innovation within the team. - Training & Support
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Provide basic and specialised training in bioinformatics to various staff groups; support training of STP trainees; troubleshoot and optimise bioinformatics resources. - Stakeholder Engagement
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Build and maintain relationships with Clinical Scientists, Genetic Technologists, Informatics Scientists, research partners, and technology providers to facilitate seamless service delivery. - Quality Assurance
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Maintain high quality standards to ensure laboratory UKAS accreditation; participate in internal audits, document control, and continuous improvement initiatives to uphold ISO 15189.
- BSc (1st or 2nd class honours) in Bioinformatics, Computer Science, Health Informatics or a relevant biological discipline with demonstrated bioinformatics and computing abilities (first or second class).
- MSc, PhD or equivalent in a relevant subject.
- HCPC registration in Clinical Bioinformatics or working toward registration.
- Experience working in a bioinformatics section of a diagnostic genetics laboratory or similar environment.
- Experience developing and implementing bioinformatics tools and resources.
- Experience in molecular genetics or diagnostic genomics services.
- Proven experience of successful project management.
- Experience in IT, applications, development, processes and organisation.
- Knowledge of Next Generation Sequencing approaches and statistical techniques for large data analysis.
- Knowl…
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