Research Software Engineer - Generative Biology Institute

Overview

At the Ellison Institute of Technology (EIT), we're on a mission to translate scientific discovery into real world impact. We bring together visionary scientists, technologists, engineers, researchers, educators and innovators to tackle humanity's greatest challenges in four transformative areas:
Health, Medical Science & Generative Biology;
Food Security & Sustainable Agriculture;
Climate Change & Managing CO₂;
Artificial Intelligence & Robotics.

This is ambitious work that demands curiosity, courage, and a relentless drive to make a difference. At EIT, you'll join a community built on excellence, innovation, tenacity, trust, and collaboration, where bold ideas become real-world breakthroughs. Explore more .org.

At EIT/the GBI we are seeking a detail oriented Research Software Engineer to help design, build, and operate the software and data systems that enable cutting-edge research in engineering biology. This is a broad, hands-on role at the interface of scientific research, software engineering, data engineering, cloud infrastructure, and high-performance computing.

Working as part of a new Scientific Computing team, the postholder will have the opportunity to shape and build systems from an early stage, rather than simply maintain established platforms. They will contribute to the development of data collection workflows, scientific software, cloud-based data infrastructure, HPC-enabled analysis pipelines, monitoring tools, and a data platform that will help researchers locate, access, and use scientific data effectively.

This role is particularly suited to someone who enjoys working across the technology stack, learning new tools and domains, and collaborating closely with scientists and engineers.
We do not expect candidates to have deep experience in every area listed in this description
. Instead, we are looking for a strong software engineer with a scientific mindset: someone who can understand research needs, communicate clearly with multidisciplinary teams, learn unfamiliar technologies quickly, and help build reliable, scalable systems that advance GBI's scientific mission.

• Design, develop, and maintain high-performance, maintainable, and reusable research software to support large-scale biomedical data analysis
• Partner with scientists to understand research workflows, develop robust and user-friendly computational tools and services that meet scientific needs, and train users in their effective application
• Help build data collection and ingestion workflows for laboratory-generated data, including heterogeneous data types, formats, and sources
• Contribute to the development of cloud-based data infrastructure, including systems for data movement, integrity, replication, monitoring, and access
• Help to deploy, scale, and optimise software and workflows across local and cloud-based HPC environments, including Slurm-based systems
• Benchmark, profile, and optimize computational workloads for maximum performance, scalability, and efficient use of hybrid HPC and cloud environments
• Explore and innovate solutions where data and computational needs are at the frontier of what is currently possible
• Apply software engineering best practices, including version control, testing, CI/CD, code review, documentation, infrastructure as code, and containerisation

Essential Knowledge,

Skills and Experience:

• Bachelor's or Master's degree in Computer Science, Computational Biology, Engineering, or a related field (PhD desirable)
• Ability to work closely with multidisciplinary research teams to deliver computational tools that advance scientific goals
• Strong communication and relationship-building skills, with the ability to work effectively across engineering teams and explain technical concepts clearly to scientists and non-specialist audiences
• Proficiency in one or more key programming languages (e.g., Python, Julia, Rust, C/C++, or Java)

Desirable Knowledge,

Skills and Experience:

• 2+ years of professional experience (or equivalent) in software engineering, preferably within a scientific or research environment
• Proven experience developing software for scientific research,…