Join an exciting biotech start-up in Edinburgh that’s developing next-generation technology relating to RNA sequencing, bioinformatics, and diagnostic development. Backed by academic expertise and driven by a mission to advance precision medicine, this agile team is developing tools to transform how RNA is discovered and analysed. As the company scales, it’s looking for a Bioinformatic Software Engineer to lead the build-out of cloud infrastructure and analysis pipelines critical to its technology platform.
This is an opportunity to join a growing, cross-functional team working on meaningful challenges in biology and data science, where your ideas and engineering skills will have a direct impact on product development and scientific discovery.
Bioinformatic Software Engineer responsibilities
Design, develop, optimise, and maintain cloud computing environments for bioinformatic data processing.
Build scalable, well-documented data analysis pipelines for long-read RNA sequencing workflows.
Develop and implement logging, reporting, and data archiving systems to support reproducible research.
Lead software engineering best practices, including testing, version control, deployment, and documentation.
Generate visualisations and reports to communicate key findings from complex transcriptomic datasets.
Collaborate closely with biologists, data scientists, and product stakeholders across the business.
Bioinformatic Software Engineer requirements:
Proven software engineering and DevOps experience within a research or R&D setting.
Strong understanding of sequencing data analysis, particularly read alignment and variant calling algorithms.
Degree educated in Computer Science, Bioinformatics, or a related field.
At least 3 years' relevant experience, ideally with RNAseq data and associated tool development.
Solid programming skills in object-oriented languages and scripting languages (e.g. Python, Perl, Bash).
Experience with software quality assurance practices such as version control, testing, and validation.
Desirable experience:
Commercial experience in a software or biotech setting.
Cloud computing experience (e.g. AWS, GCP, or Azure).
Familiarity with Unix/Linux systems.
Knowledge of transcriptomic technologies such as Illumina, PacBio, or Nanopore.
Understanding of transcriptome annotation and the impact of alternative splicing.
Skills in R, C++, or similar for statistical analysis and visualisation.
Personal Attributes:
Curious and proactive, with a desire to learn and ask questions.
Strong communicator, able to collaborate across disciplines.
Thoughtful problem-solver with a strategic mindset.
Open, respectful, and team-oriented in working style.
This is a rare chance to join a well-supported start-up at an exciting stage of growth. You will be working on complex scientific problems with a direct line to product impact, in a collaborative environment where your contributions will shape the company’s direction and technology.
£Comp + company benefits
Bioinformatics/Software Engineering/RNA Seq/Python
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