UK

United Kingdom · Research and development · Director/VP (16-20 years)

Director, Global Research Infrastructure

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  • Experience bandDirector/VP (16-20 years)
  • Reports toVP, R&D Technology & Operations
  • UK framework levelUsually a director, accountable for a division and its numbers

Also advertised as VP of Research Computing · Head of R&D Technology · Global Head of Scientific Platforms

Built on 43,079 real UK job descriptions we analysed · grounded in what real qualifications cover

Two short quizzes about you

1From this job to a course

The qualifications matched to this job

OTHM Level 7 Diploma in Data Science OTHM Qualifications · Level 7 · covers 2 of 4 standards
NCC Education Level 5 Extended Diploma in Computing with Data Science NCC Education Limited · Level 5 · covers 1 of 4 standards
Level 6 Award in Data-led Decision Making Institute of Sales Professionals · Level 6 · covers 1 of 4 standards
Pearson BTEC Level 5 Higher National Diploma in Computing for England Pearson Education Ltd · Level 5 · covers 1 of 4 standards
Pearson BTEC Level 5 Higher National Diploma in Digital Technologies Pearson Education Ltd · Level 5 · covers 1 of 4 standards

Matched from the standards this job is measured against: a suggestion, not an official ruling.

The units you would start with

Data Science Foundations OTHM Level 7 Diploma in Data Science
Introduction to Data Science and Big Data NCC Education Level 5 Extended Diploma in Computing with Data Science
Data-led Decision Making Level 6 Award in Data-led Decision Making
Apply the Concepts of Data Science to Computer Engineering NOCN Level 5 Diploma in Computer Engineering (Information Technology and Data Science)
Data Analytics Pearson BTEC Level 5 Higher National Diploma in Computing for England

The future skills this job leans on

AI Fluency working with AI as a thinking partner
Data Fluency turning numbers into a decision
Automation Fluency building AI into how work runs
Frontier Fluency the next wave, beyond mainstream AI
Foresight Fluency seeing round the corner
Your Plan Illustration

Built for Director, Global Research Infrastructure

5 units that map to this job, from the qualifications that cover it.

  1. Data Science Foundations OTHM Qualifications · covers 2 of 4 standards Level 7
  2. Introduction to Data Science and Big Data NCC Education Limited · covers 1 of 4 standards Level 5
  3. Data-led Decision Making Institute of Sales Professionals · covers 1 of 4 standards Level 6
  4. Apply the Concepts of Data Science to Computer Engineering NOCN · covers 1 of 4 standards Level 5
  5. Data Analytics Pearson Education Ltd · covers 1 of 4 standards Level 5
These are the real units behind this job, in the order they rank for it. Nothing here is marked done, because this plan has not been started by anyone yet. Yours would fill in as you go.

2AI and this work

Will AI change your work as a Director, Global Research Infrastructure?

Nobody can say exactly how. Here is what this job is being asked for next, and where to start.

The new skills this role is being asked for

  • AI/ML Strategy for Autonomous Labs & Research Automation
  • Quantum Computing Readiness & Impact Assessment
Why each one is rising

The future skills this job leans on

We'll only ever tell you what we can actually back up. No hype, no scare tactics.

What happens when you start

Next, a free account. We build your Director, Global Research Infrastructure plan as you set up, starting with the free Automation Fluency module. No card.

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3What this role really is

Director of Global Research Infrastructure plans and runs the technology that supports scientific research, from computing systems to lab equipment.

4What you'd actually use

The tools this job runs on, and how well you'd need to know each one.

HPC & Workload Management (Slurm/SGE, AWS ParallelCluster, Azure CycleCloud) Strategic

Leading platform decisions (e.g., on-prem vs. cloud burst), modelling TCO for HPC solutions, and setting global standards for workload management and optimisation.

Lab Informatics Platforms (Benchling, LabWare, Dotmatics) Strategic

Owning the enterprise lab informatics roadmap, selecting and negotiating contracts for next-gen platforms, and ensuring GxP compliance of these systems globally.

Storage Systems (NetApp, Isilon, AWS S3/Glacier) Strategic

Developing the global data storage and sovereignty strategy, approving multi-million pound storage hardware refresh cycles, and defining data lifecycle management policies for petabyte-scale data.

Infrastructure as Code (Terraform, Ansible) Strategic

Mandating and governing the use of IaC across all R&D infrastructure to ensure reproducibility, compliance, and efficient deployment of complex research environments.

Financial/GRC Platforms (Anaplan, ServiceNow GRC) Expert

Using Anaplan for CapEx/OpEx budget planning and forecasting across your global function. Leveraging ServiceNow GRC to manage system validation, compliance documentation, and audit trails for regulated systems.

Cloud Platforms (AWS, Azure, GCP) Expert

Defining the multi-cloud or hybrid cloud strategy for research infrastructure, optimising cloud spend, and overseeing the deployment of cloud-native scientific workloads at scale.

5What you get to decide, and how that grows

Power in a job isn't your title. It's what you're allowed to decide. Here's how it grows as you move up.

The choiceComing in Where you are nowThe step above
Strategic Infrastructure Investment (e.g., new HPC cluster, global LIMS) No authority. Assists with data gathering for business case. Proposes technical solutions and provides cost estimates for components. Designs technical architecture and makes recommendations to leadership, justifying technical choices.
Organisational Design & Team Structure No authority. Operates within existing team structure. No authority. Provides feedback on team processes. No authority. May suggest improvements to team workflows.
GxP System Validation Strategy No authority. Follows established validation protocols. Executes validation tests and documents results for specific systems. Develops validation plans (IQ, OQ, PQ) for new systems and ensures adherence to GxP guidelines.

6How you'll be judged

The scoreboard, and what is not on it. The hard targets, how often each is actually looked at, and the quiet signals that never reach a dashboard.

Research Computing Total Cost of Ownership (TCO) Reduction
Optimising the overall spend on compute, storage, and lab informatics, balancing performance with cost efficiency.
Target · Achieve a 10-15% reduction in TCO for research computing over a 3-year period, year-on-year improvements.

Through cloud migration and resource optimisation, you reduced our HPC cloud spend by £1.5M in FY24 while maintaining performance levels, contributing to a 12% TCO reduction.

Infrastructure Programme Delivery & Budget Adherence
Successful delivery of major infrastructure programmes (e.g., new global HPC cluster, enterprise LIMS rollout) within agreed timelines and budget.
Target · Deliver 90% of strategic infrastructure programmes on-time and within 5% of the approved budget.

The global data lake programme was delivered 2 weeks ahead of schedule and £150K under its £2M budget, providing a new platform for 500+ scientists.

Research Data Processing Time Reduction
Improving the speed at which our scientists can process and analyse large datasets, directly impacting research cycle times.
Target · Reduce average end-to-end data processing time for critical scientific workflows by 15-20% over 18 months.

After optimising storage IOPS and HPC scheduler configurations, average genomic sequencing analysis time dropped from 48 hours to 36 hours, a 25% improvement.

Infrastructure Stability & Compliance
Maintaining a highly stable and compliant research infrastructure environment, minimising unplanned downtime and ensuring audit readiness.
Target · Achieve >99.9% uptime for critical research systems (HPC, LIMS, ELN) and zero critical findings in GxP system audits.

Your team maintained 99.98% uptime across all regulated systems last year and passed the MHRA GxP audit with no observations related to infrastructure validation.

R&D Leadership Satisfaction & Strategic Influence
How well your infrastructure strategy aligns with and enables the broader R&D scientific goals, and how effectively you communicate and gain buy-in from senior R&D leaders.
  • You're regularly invited to R&D leadership strategy sessions. Your proposals for infrastructure investment are consistently approved because they clearly link to scientific outcomes. R&D leaders proactively seek your advice on new research initiatives, confident in your ability to provide the necessary technological foundation.
Global Team Leadership & Development
Your ability to build, mentor, and inspire a high-performing global team of managers, architects, and engineers, fostering a culture of innovation and accountability.
  • Your direct reports consistently meet their performance goals and show clear career progression. There's a noticeable increase in cross-regional collaboration within your teams. You're seen as a fair and supportive leader who empowers their managers to make decisions and grow their own teams.
Vendor & Partner Relationship Management
Effectively managing relationships with key technology vendors and external partners to ensure we get the best value, service, and strategic alignment.
  • You've negotiated favourable terms on multi-year contracts, leading to significant cost savings. Vendors see you as a strategic partner, not just a customer, and bring you early access to new technologies. You've established robust service level agreements (SLAs) that are consistently met.
Proactive Risk Management & Innovation
Identifying and mitigating potential infrastructure risks before they become problems, while also championing the adoption of new technologies that can give us a competitive edge.
  • You've implemented a robust disaster recovery plan that has been successfully tested. You're regularly presenting proposals for pilot programmes with emerging technologies (e.g., AI-specific hardware, quantum readiness). Your team proactively identifies and addresses 'Rogue IT' before it becomes a security or compliance issue.

7Would you like it

Both sides. What people enjoy, and what grinds them down.

What people enjoy
Enabling Scientific Breakthroughs

You get a real kick out of seeing your infrastructure decisions directly accelerate a research project or enable a new type of experiment. It's not just about the tech; it's about the science it supports.

You feel a genuine sense of accomplishment when a new HPC cluster you championed allows a team to run simulations in hours that used to take days, directly leading to a new drug candidate.

Strategic Impact & Organisational Building

You thrive on setting the multi-year vision, shaping how a global R&D organisation operates, and building high-performing teams and capabilities. You're a builder of systems and people.

You're energised by the challenge of designing a global data strategy that will serve the company for the next decade, and then seeing your team grow and deliver on that vision.

Solving Complex, Multi-faceted Challenges

You enjoy tackling problems that involve deep technical knowledge, significant financial implications, and complex human dynamics (e.g., getting diverse scientific groups to agree on a common platform).

You relish the puzzle of optimising cloud spend across dozens of research projects, each with unique requirements, while ensuring compliance and performance—it's a constant balancing act.

What frustrates people
  • The constant tension between researchers who demand administrative rights to install anything and the security team who wants to lock everything down tight.
  • Being blamed for project delays when, in reality, the issue is poorly written, inefficient scientific code that consumes 100x more resources than it should.
  • Dealing with legacy scientific instruments that only run on an unsupported Windows XP machine, which is a massive security risk but essential for an ongoing, critical study.
  • The end-of-quarter scramble to spend CapEx budget before it's lost, sometimes leading to rushed purchasing decisions that aren't perfectly optimised.
  • Explaining to regulators why our 'validated state' documentation is 1000 pages long and why every tiny change requires a mountain of paperwork.
What this role does not give you
  • A purely technical, hands-on engineering role; you'll be leading and strategising more than coding or racking servers.
  • A predictable, calm environment where all decisions are clear-cut and universally agreed upon.
  • A role where you can avoid complex financial negotiations or difficult conversations about resource allocation.
  • The luxury of building 'perfect' solutions without considering cost, timeline, or political realities.

8Who you work with

This role shapes the entire R&D pipeline's efficiency, compliance, and innovation capacity across our global business unit. Your decisions directly influence how fast and effectively our scientists can operate, impacting everything from early-stage discovery to clinical trial support. Get it right, and we accelerate drug discovery; get it wrong, and we face significant delays, compliance risks, and wasted investment.

Inside the business
  • R&D Leadership Team (Heads of Therapeutic Areas, Chief Scientific Officer)
  • Finance Director and their team (for budget approval and financial governance)
  • Legal and Compliance teams (for GxP, data privacy, and intellectual property)
  • IT Security (for protecting our research data and systems)
  • Programme Managers (for aligning infrastructure delivery with research milestones)
  • Procurement (for vendor selection and contract negotiation)
Outside the business
  • Key Technology Vendors (e.g., AWS, Azure, Dell, NetApp, specialised lab system providers)
  • Industry Consortia and Standards Bodies (for best practices and emerging tech)
  • Regulatory Bodies (ensuring our systems meet GxP audit requirements)
  • Academic and Research Partners (for collaborative infrastructure projects)

9What you need before you start

Not a wish list. The things you would be expected to already have.

  • Proven experience (16-20 years) in R&D IT or scientific computing, with at least 5-7 years in a senior leadership role managing managers and large, complex budgets (£2M+).
  • Demonstrable experience in defining and executing global infrastructure strategies for a large, multi-national organisation.
  • A track record of successfully delivering major infrastructure programmes (multi-million pound projects) on time and within budget.
  • Deep expertise in GxP compliance and system validation within a regulated R&D environment.
  • Experience building and leading high-performing global teams, fostering a culture of accountability and continuous improvement.
  • Exceptional communication and influencing skills, with a proven ability to engage effectively with C-suite executives, scientific leaders, and external partners.

10What to practise next

Where the job is going, and what to do about it starting this week.

Advanced Cloud-Native Architectures & Multi-Cloud Orchestration

While we're already in the cloud, the next frontier is truly cloud-native, serverless HPC, and seamlessly orchestrating workloads across multiple cloud providers (and on-premise). This is about maximising flexibility, resilience, and cost-efficiency at a global scale.

Serverless HPC · Multi-Cloud & Hybrid Cloud Orchestration · Containerisation & Kubernetes at Scale · Cloud Security Posture Management (CSPM)

  • This quarter: Review current cloud spend and identify top 3 areas for serverless or multi-cloud optimisation; task your lead architects with proof-of-concept designs.
  • Next 6 months: Develop a multi-cloud strategy document, outlining the business case and technical roadmap; begin pilot projects for serverless HPC workloads.
  • Next 12 months: Establish a Cloud Centre of Excellence (CCOE) within your team to drive best practices and governance for advanced cloud architectures.
  • Ongoing: Engage with cloud provider executive teams to understand their roadmap and influence features relevant to R&D.

Quick win: Identify one non-critical scientific workflow that could be migrated to a serverless function (e.g., AWS Lambda, Azure Functions) to test the concept and demonstrate cost savings.

Advanced Data Governance, Ethics & Synthetic Data

As AI becomes more pervasive and data volumes explode, the ethical implications of data use, robust governance, and the strategic use of synthetic data become paramount. You'll need to lead the infrastructure aspects of these complex areas.

AI Ethics & Responsible AI · Synthetic Data Generation & Management · Data Mesh & Data Fabric Architectures · Data Lineage & Provenance at Scale

  • This quarter: Collaborate with Legal and Compliance to review our current data governance framework for AI-specific considerations; identify potential gaps.
  • Next 6 months: Sponsor a research project or pilot to explore synthetic data generation for a specific sensitive dataset; evaluate tools and platforms.
  • Next 12 months: Develop a strategic framework for 'Responsible AI Infrastructure', outlining principles and technical requirements for ethical data use.
  • Ongoing: Participate in industry forums on data ethics and synthetic data, influencing best practices and staying ahead of regulatory trends.

Quick win: Implement automated data lineage tracking for one critical scientific workflow, providing clear visibility into data transformations from instrument to insight.

11Staying current once you are in

What people here do to keep up
  • Regularly attending executive-level industry conferences (e.g., Bio-IT World, Gartner IT Symposium) to stay abreast of strategic trends and network with peers.
  • Participating in leadership development programmes focused on executive presence, strategic negotiation, and managing global teams.
  • Engaging with academic institutions or consortia involved in cutting-edge research computing or lab automation to foster partnerships and identify emerging technologies.
  • Mentoring rising talent within the organisation, both within your direct teams and across other departments, to build leadership capability.

12The rising capability

The rising capability

Zavmo analysis

What's rising in its place

This is where the work is heading, and the higher pay with it. Get fluent here and the shift stops being a threat and starts being your edge.

AI/ML Strategy for Autonomous Labs & Research Automation

The shift towards 'autonomous labs' and AI-driven experimental design is accelerating. Infrastructure leaders need to move beyond just supporting existing AI workloads to strategically enabling and integrating AI into every facet of research operations, from instrument control to data analysis pipelines. This is about transforming how science is done.

  • AI-driven Experimental Design
  • Robotics & Lab Automation Integration
  • Real-time Data Streaming & Edge Computing
  • AI Model Lifecycle Management (MLOps)

Quantum Computing Readiness & Impact Assessment

While still nascent, quantum computing has the potential to revolutionise drug discovery, materials science, and complex simulations. As a Director, you'll need to understand its potential impact, assess when it becomes a viable tool for our research, and begin to lay the groundwork for future integration, even if it's 5-10 years out. This is about strategic foresight.

  • Quantum Algorithms for Drug Discovery
  • Hybrid Quantum-Classical Computing
  • Quantum Computing as a Service (QCaaS)
  • Quantum-Safe Cryptography

13What you’ll use

What you’ll use

Skills this role draws on

Technical

  • GxP Compliance & System Validation (CSV)
  • HPC Architecture & Optimization
  • FAIR Data Principles & Scientific Data Lifecycle Management
  • Capital Expenditure (CapEx) Planning & Justification
  • Cloud FinOps for Research
  • Global Lab Informatics Strategy

14The pathway

The pathway

How you actually get there, here

How you become one varies far more by country than what one does. This is the UK route. Most people take one of these ways in; the right one depends on where you're starting from.

  1. 1

    Senior Manager, Research Computing (from a large organisation)

    3-5 years as a Senior Manager

    Skills to master

    • Moving from managing a large team to managing managers, owning a significant P&L, developing multi-year strategic roadmaps, and presenting to executive leadership. You'd need to broaden your scope beyond a single domain (e.g., just HPC) to cover all R&D infrastructure.

    You're ready to move on when

    • Successfully led a major infrastructure programme (£1M+ budget) from conception to delivery.
    • Consistently met or exceeded financial targets for your managed function.
    • Developed and mentored at least two direct reports into more senior leadership roles.
    • Demonstrated ability to influence cross-functional stakeholders at a senior level.
  2. 2

    Head of IT/Infrastructure (from a smaller biotech or pharma company)

    4-6 years as Head of IT/Infrastructure

    Skills to master

    • Scaling your experience from a smaller company to a global enterprise, navigating more complex organisational politics, managing significantly larger budgets and teams, and operating within a more stringent regulatory framework. You'd also need to develop deeper specialisation in specific R&D infrastructure domains.

    You're ready to move on when

    • Successfully built and scaled infrastructure for a growing R&D organisation.
    • Managed all aspects of IT/infrastructure, including strategy, budget, and operations.
    • Demonstrated strong vendor management and negotiation skills.
    • Proven ability to attract and retain technical talent.
  3. 3

    Lead Research Infrastructure Architect (from a very large organisation)

    5-7 years as a Lead/Principal Architect

    Skills to master

    • Transitioning from a purely technical, individual contributor role to a leadership position with P&L accountability, people management responsibilities (of managers), and executive stakeholder engagement. You'd need to develop strong business acumen and strategic planning skills.

    You're ready to move on when

    • Architected and overseen the implementation of multiple complex, enterprise-scale research infrastructure solutions.
    • Consistently influenced technical direction across multiple teams or departments.
    • Mentored numerous junior architects and engineers.
    • Demonstrated a strong understanding of the business impact of architectural decisions.

15Where this role leads

The long view: This role can lead to wider technology leadership, such as Chief Technology Officer or Chief Operating Officer roles overseeing research operations.

The ten Future Fluencies

Zavmo analysis

The credential is what you can do today. These are what keep you valuable.

A qualification proves you can do the job as it's defined today. These ten are what decide whether you're still the obvious person for it in five years. They're the capabilities employers are now writing into senior roles faster than people are learning them. Zavmo weaves them through whatever you study, so you come out with both: the credential and the fluency.

The highlighted ones are the Fluencies your role leans on hardest, from how Director, Global Research Infrastructure is actually changing.

Where it leads

Roles this leads to

The record names a next step, but the catalogue has no page for it yet:

  • VP, R&D Technology & Operations

How you would learn this

One to one, on the work you already do

A tutor sets the task against your own job and marks the reasoning, at your pace. There is no cohort to fall behind.

A lesson from Data Science Foundations, worked against Director, Global Research Infrastructure.

Data Science Foundations Level 7

Applied to your work in Director, Global Research Infrastructure

1. To enable the learner to define the scope and landscape of Data Science and differentiate the roles of Data Scientists from other IT professionals. 2. To enable the learner to evaluate key topics within Data Science, including data administration, governance, and big data sources. 3. To enable the learner to describe the architecture and core elements of Apache Hadoop. 4. To enable the learner to analyse the advantages and disadvantages of utilising Artificial Intelligence techniques in a business context. 5. To enable the learner to critically analyse the impact of Big Data on digital transformation within organisations and its effects on users. 6. To enable the learner to review strategies for ensuring data compliance and explain the responsibilities and challenges faced by data specialists.

How the thinking builds
  1. 1 Remember
  2. 2 Understand
  3. 3 Apply
  4. 4 Analyse
  5. 5 Evaluate
  6. 6 Create
An illustration of a Zavmo lesson, built from this role’s own route. The unit, its objective and every criterion above are the awarding body’s own words, not an example.

It is £70 a month, billed monthly. Your free first module is Future Fluency, and you can cancel any time.

See Your Progress Grow Illustration
Director, Global Research Infrastructure
  • GxP Compliance & System Validation (CSV)
  • HPC Architecture & Optimization
  • FAIR Data Principles & Scientific Data Lifecycle Management
  • Capital Expenditure (CapEx) Planning & Justification
  • Cloud FinOps for Research
  • Global Lab Informatics Strategy
This is your Mind Palace on learn.zavmo.ai. Every skill above comes from this role's own record, not an example borrowed from another job. A node lights up when you evidence it, and what you build stays yours between jobs. That is the part a course cannot do.

16The detail, folded away

Everything else the record holds

The career branches in full, how AI is already showing up in the day-to-day, and the questions people ask about this job. Here when you want them, out of the way while you decide.

Where it leads next, rung by rung

Where it leads

The career path, and where it branches

Director, Global Research Infrastructure is a start, not a ceiling. Each step below asks for new skills and hands back more autonomy.

  1. VP, R&D Technology & Operations

    3-5 years in the Director role

    This is the next natural step, moving from managing global infrastructure to overseeing all technology and operations for the entire R&D pipeline.

    • Strategic oversight of R&D data science and AI platforms.
    • Leadership of R&D programme management and portfolio optimisation.
    • Deep understanding of clinical operations technology.
    • Global regulatory affairs for R&D technology.
Working with AI on the job

Working with AI

Where AI is starting to help

As a Director, your time is precious. It's about strategic thinking, leadership, and high-level problem-solving, not getting bogged down in administrative tasks or sifting through endless reports. Good news: AI is here to give you back valuable hours every week, letting you focus on what truly matters.

Imagine having a co-pilot that helps you make sense of complex data, draft critical documents, and even anticipate infrastructure issues. For a Global Research Infrastructure Director, AI isn't just a nice-to-have; it's a strategic advantage that helps you govern a multi-million pound budget, manage global teams, and keep our research ahead of the curve.

Predictive Infrastructure Monitoring

Use AI/ML models, often built into platforms like Datadog or Splunk, to analyse telemetry from your HPC clusters and storage systems. This helps you predict component failures or performance bottlenecks before they impact critical research jobs, shifting your team from reactive firefighting to proactive problem-solving. You'll get early warnings, allowing your managers to intervene strategically.

Cloud Cost Anomaly Detection

Deploy AI-powered FinOps tools to automatically detect anomalous cloud spending in real-time. This means catching a misconfigured analysis pipeline consuming thousands of pounds per hour immediately, triggering alerts to your team. No more nasty surprises on the monthly cloud bill; you'll maintain tighter control over your multi-million pound OpEx budget.

Vendor & Tech Spec Synthesis

Use Large Language Models (LLMs) to rapidly ingest, summarise, and compare dense technical documentation, whitepapers, and vendor proposals for new technologies. Imagine asking, 'Compare the key features and limitations of Lustre versus GPFS for our cryo-EM workflow, considering cost and scalability.' This accelerates your technology evaluation and RFI/RFP processes significantly, helping you make better strategic choices faster.

Budget Justification & Policy Drafting

Leverage generative AI to create first drafts of complex, high-stakes documents. This could be a capital budget request for a new global storage platform or a new data governance policy. AI can translate your technical needs into business-friendly language, saving you hours on the 'blank page' problem for administrative and strategic writing that goes to the C-suite or board.

Common questions

Common questions

How do you become a Director, Global Research Infrastructure?

Common routes in include Senior Manager, Research Computing (from a large organisation) (3-5 years as a Senior Manager), Head of IT/Infrastructure (from a smaller biotech or pharma company) (4-6 years as Head of IT/Infrastructure) and Lead Research Infrastructure Architect (from a very large organisation) (5-7 years as a Lead/Principal Architect). Times vary with prior experience.

Where can a Director, Global Research Infrastructure progress to?

This role can lead on to VP, R&D Technology & Operations (3-5 years in the Director role), depending on the skills you build.

What new skills matter most for a Director, Global Research Infrastructure?

Increasingly, AI/ML Strategy for Autonomous Labs & Research Automation and Quantum Computing Readiness & Impact Assessment. These are the skills our record of this role lists as growing.

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17Where to go from here

Other roles at Level 7

Same depth of qualification, different job. Useful if the work appeals but this particular role does not.

 More jobs in research and development

Stay in the field you know and move sideways rather than up.
If you leave this industry

Skills in managing complex, regulated infrastructure within research and development carry across sectors. Similar leadership roles exist in defence, aerospace, and large academic research institutions. Data management, high-performance computing, and compliance work the same way in each.

This role profile is © 2026 Growth Engineering Technologies Ltd. Built from UK occupational standards and regulated qualification data, and written for Zavmo.

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