Bioinformatician / Computational Scientist ISOgenix Scientist Oxford

About ISOgenix

We are an Oxford University spin-out developing breakthrough therapies for the treatment of ALS and other neurodegenerative diseases. Our approach builds upon novel protein isoform insights identified using our state-of-the-art technologies including long read sequencing and proprietary bioinformatics pipelines. Our founding team has decades of experience in the field of precision medicines, and we have an unwavering focus on developing novel therapies for patients. We are based in Oxford, UK.

Summary of Position

We’re looking for a highly talented and motivated Bioinformatician / Computational Scientist with a strong biology background to join us. In addition to possessing highly relevant expertise, the successful applicant will share our passion for groundbreaking science and be keen to work in a small but growing biotechnology team. They will work collaboratively, openly and be keen to take on new responsibilities as our science progresses and business grows. This position is hybrid, with a requirement to be on site at least one day a week.

Responsibilities

• Collaborating closely with internal scientists and external partners to design, implement, and improve custom bioinformatics workflows, scripts, and analysis tools to support target discovery and drug development.
• Developing, maintaining, and extending bioinformatics pipelines for the analysis of sequencing data generated from Illumina and PacBio platforms, including ad hoc analyses to address specific biological questions (e.g. novel exon discovery, isoform usage, splicing changes).
• Writing and modifying code (e.g. in R, Python, or related languages) to perform bespoke data analyses beyond standard, off-the-shelf bioinformatics tools.
• Supporting the use of cloud-based computing environments (e.g. AWS) for running and scaling bioinformatics workflows and managing large sequencing datasets.
• Contributing to the organisation, storage, and management of bioinformatics data, ensuring data integrity, reproducibility, and traceability.
• Analysing and interpreting genomics and transcriptomics data in a disease-relevant biological context and translating results into actionable insights for experimental follow-up.
• Communicating results clearly to both computational and experimental collaborators through written reports, visualisations, and presentations at team meetings.

Qualifications

• A PhD in Computational Biology, Bioinformatics, Computer Science, or a related field, with experience in transcriptomics analysis.
• Experience with mammalian genomics and transcriptomics; experience with human genomics and transcriptomics is required.
• Good understanding of human disease biology and genetics.
• Practical experience analysing NGS datasets, including DNA- and RNA-sequencing data, with hands‑on experience in analyses such as variant calling, differential expression, and pathway or functional analysis, and interpretation of results in a biological context; experience with single‑cell RNA‑seq and/or splicing analysis is a plus.
• Experience building and maintaining bioinformatics workflows that combine custom scripts with public datasets and bioinformatics tools, using workflow management systems (e.g. Snakemake, Nextflow).
• Proficiency in R and/or Python, with a solid understanding of statistical methods for biological data analysis and demonstrated ability to write and modify custom code to perform bespoke and ad hoc analyses beyond standard bioinformatics tools.
• Experience delivering multiple analysis projects in parallel in a fast‑paced, deadline‑driven environment.
• Strong attention to documentation and organisation, with the ability to maintain clear, well‑structured records of bioinformatics pipelines, analyses, and reports to support reproducibility and traceability.
• Strong communication skills, with the ability to explain complex analyses to both computational and experimental scientists.
• Experience with long read RNA sequencing data analysis (e.g. PacBio ISO‑Seq), including de novo isoform discovery, transcript quantification and splicing analysis.
• Experience demonstrated through publicly available projects (e.g. GitHub) is a plus.
• Background in neurological / neurodegenerative disease biology.
• Experience working in a multidisciplinary team (e.g. involving clinicians, experimental scientists, and computational scientists) and/or in a broader collaborative research and operational environments.
• Familiarity with cloud‑based computing environments (e.g. AWS) and databases (SQL) for genomics data processing and storage.

We are committed to creating an inspiring and supportive work environment. As a Bioinformatician, you will enjoy:

• Competitive salary and benefits package.
• A healthy work‑life balance.
• Continuous professional development and learning opportunities.
• An open, collaborative and supportive working environment.
• Working in a small dynamic team with the opportunity to ultimately make a significant impact on the development of new medicines for diseases with significant unmet need.

How to Apply

If you’re excited to join us, please submit your CV along with a brief cover letter addressing the following question. Applications will be reviewed on a rolling basis, and we aim to fill the position promptly. We therefore encourage qualified candidates to apply as soon as possible. Please describe a project in which you designed, modified, and implemented a bioinformatics analysis pipeline and/or performed custom coding or ad hoc analyses. In your response, indicate:

• The type of data analysed (e.g. human transcriptomics, RNA‑seq; specify short‑read and/or long‑read if applicable)
• Brief description of custom analyses or code you developed beyond standard tools (please include a link to GitHub or a similar repository, if applicable)
• The biological question being addressed and how the analysis informed biological understanding or downstream decisions.

Please note: You are welcome to keep your response high level and should not include any confidential or proprietary information.