Research Software Engineer - Generative Biology Institute at Ellison Institute of Technology

Oxford, England, United Kingdom -

Full Time

Start Date

Immediate

Expiry Date

20 Aug, 26

Salary

0.0

Posted On

22 May, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Yes

Skills

Python, Julia, Rust, C/C++, Java, Cloud Infrastructure, High-Performance Computing, Data Engineering, CI/CD, Containerization, GPU Optimization, Machine Learning Frameworks, Workflow Management Systems, Biomedical Data Analysis, Software Architecture, Version Control

Industry

Research Services

Description

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 - 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. Together, we push boundaries, embrace complexity, and create solutions to scale ideas from lab to society. Explore more at www.eit.org. Welcome to the Generative Biology Institute: Led by Founding Director Jason Chin, the Generative Biology Institute (GBI) at the Ellison Institute of Technology is tackling the key challenges in making biology engineerable, and thereby unlocking the unrivalled power of biology for the benefit of humanity. The vision of the GBI is to lay the foundations for engineering biology, and unlock its potential for good. To achieve this, we must overcome two key challenges. First, we need the ability to write in the natural language of biology, enabling the rapid and scalable synthesis of entire genomes with precision. Second, we must understand what to write - determining which DNA sequences will generate biological systems that perform the desired functions. Addressing these challenges will allow us to harness the full power of biology to create transformative solutions across health, agriculture, clean energy and more. GBI will have sustained and substantial funding to support the unique scale and ambition of its ground-breaking vision for engineering biology. GBI researchers will also be supported by cutting-edge technology hubs including mass spectrometry, flow cytometry, sequencing, automation, imaging, and bioprocessing. GBI will also have access to substantial compute resources that can be leveraged to further accelerate progress, including scientific compute, bioinformatics, and machine learning. The environment at GBI will allow researchers to undertake ambitious, long-term, collaborative research, and we will actively support the translation of research to commercial applications, where appropriate. The Generative Biology Institute commenced operations in 2025, occupying newly renovated bespoke space in the Oxford Science Park. The team will later move to a purpose-made facility in the Oxford Science Park, currently under construction. Once complete, this state-of-the-art facility will include more than 40,000 m² of research laboratory and office space. It will house over 30 groups and up to 600 employees at scale, focused on solving the two critical challenges in making biology engineerable and applying the solutions to addressing the global challenges encapsulated in EIT’s Humane Endeavors. Your Role: At EIT/the GBI we are seeking a detail orientated 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. Key Responsibilities 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, data analysis, or computational biology. Familiarity with parallel and distributed computing frameworks and techniques (MPI, CUDA, OpenMP, etc). Experience in GPU optimisation and/or machine learning frameworks. Experience working with workflow management systems (Nextflow, Snakemake, CWL, or WDL), ideally in the fields of bioinformatics, computational biology, scientific computing, or data science workflows. Experience integrating software into HPC and/or cloud environments (OCI, AWS, GCP, Azure, or hybrid systems). Strong understanding of modern software engineering practices, including CI/CD, testing, and containerization. Our Benefits: Salary: Competitive + travel allowance + bonus Enhanced holiday pay Pension Life Assurance Income Protection Private Medical Insurance Hospital Cash Plan Therapy Services Perk Box Electric Car Scheme Working Together – What It Involves: You must have the right to work permanently in the UK with a willingness to travel as necessary. In certain cases, we can consider sponsorship, and this will be assessed on a case-by-case basis. You will live in, or within easy commuting distance of, Oxford (or be willing to relocate). During peak periods, some longer hours may be required and some working across multiple time zones due to the global nature of the programme. We have a hybrid policy in place, minimum 3 days a week on site

Responsibilities

Design, build, and operate software and data systems to support large-scale biomedical research in engineering biology. This includes developing data collection workflows, cloud-based infrastructure, and optimizing computational workloads on HPC environments.