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    • Responsibilities include assisting our Technical Project Managers with the Configuration and management of network products including:
    • Act as an escalation point for infrastructure incidents, troubleshooting and resolving complex technical issues efficiently.
    • One paid volunteering day per year.
    • Background or experience as software engineer for 1-2 years.
    • Work with the AI Deployment Engineer to hand off anything requiring deep infrastructure.
    • Support onboarding of new offices, network services or infrastructure changes.
    • Proven experience in a NOC, network operations, or infrastructure support role.
    • Modern cancer research increasingly depends on robust, scalable and well-managed computational infrastructure.
    • Interest free season ticket loans.
    • Work within established configuration and change management policies to ensure awareness, approval and success of changes made to the network infrastructure.
    • Assist with infrastructure design and site deployments.
    • Ensure infrastructure aligns with security standards and best practices.
    • Based within 20 miles of Canvey Island, Essex.
    • Nationwide installations | Company Van | Training | Career Progression.
    • No two weeks are the same.
  • View similar jobs with this employer
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    • Provide technical leadership and mentorship to junior engineers.
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    • Full clean UK driving license.
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    • Handle advanced onboarding, migrations, and client infrastructure projects where required.
    • Support, guide and mentor all engineers on complex issues and…

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Job Post Details

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Senior Research Software Engineer - job post

University of Oxford
4.3 out of 5 stars
Oxford OX3 7BN
£49,119 - £63,489 a year - Full-time, Fixed term contract

Location

Oxford OX3 7BN

Full job description

The Centre for Human Genetics is seeking an experienced Senior Research Software Engineer to help shape the next generation of the Multi-Dimensional Viewer (MDV) platform, an open-source, web-based system used internationally to explore high-dimensional biological data such as single-cell and spatial omics, genomics, and imaging. MDV is used across academia and industry to democratise biological data analysis and visualisation. In this role, you will act as the technical lead for MDV’s analysis and AI capabilities, playing a central part in defining the platform’s technical roadmap and standards.
You will lead the development of Python-based analysis frameworks that enable MDV workflows, such as differential expression, spatial statistics, and re-clustering, to run as remote jobs on institutional compute infrastructure. You will contribute to the design and implementation of ChatMDV, exposing MDV’s analysis tools through a safe, LLM-based interface, and lead the integration of data versioning to support snapshotting, rollback, and full auditability of projects. Working closely with software engineers, DevOps teams, and experimental collaborators, you will provide technical leadership, contribute to documentation and strategy, promote best practice in data governance and reproducibility, and support publications, grants, and stakeholder engagement.
It is essential that you hold a postgraduate qualification in computer science, engineering, mathematics, physics, bioinformatics, computational biology, or a closely related discipline. You will bring exceptional Python expertise for scientific computing or backend development, alongside experience building robust, data-intensive workflows using sound software engineering practices. You will have a clear interest in AI and large language models, with evidence of engagement through projects, experimentation, or early research use, and a strong motivation to apply these approaches to real biological data problems. You will be comfortable working in multidisciplinary environments, communicating complex technical concepts to non-specialists, and managing your own workload to deliver high-quality outputs to deadline. Experience with biological data analysis, data versioning, containerisation, orchestration tools, or LLM-related frameworks would be an advantage.
Applications for this vacancy should be made online and you will need to upload a supporting statement and CV. Your supporting statement must explain how you meet each of the selection criteria for the post using examples of your skills and experience. Please restrict your documentation to your CV and supporting statement only. Any other documents will be requested at a later date.
This position is offered full time on a fixed term contract for 36 months and is funded by the Small Research Facility
Only applications received before 12 midday on 3 February 2026 will be considered. Please quote 184173 on all correspondence.
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