Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

High Performance Computing Senior Researcher

Fujitsu Research
Slough
1 year ago
Applications closed

Related Jobs

View all jobs

Group Leader: Artificial Intelligence (AI) in Biology

(Senior) Research Scientist - Large Language Models for Genomics

Senior Data Scientist, Model Customization, Generative AI Innovation Center, Model Customization

Senior Data Scientist, Generative AI Innovation Center, AWS Generative AI Innovation Center

2026 Machine Learning Center of Excellence (Time Series & Reinforcement Learning) - Summer Associate

Group Leader: Artificial Intelligence (AI) in Biology

Are you someone who enjoys using your research mindset to explore and innovate? Do you want to collaborate with committed people and achieve results together to develop truly human centric innovation?



Well, here at Fujitsu Research of Europe (FRE), we are combining research and industrial innovation to transform businesses and society. FRE is a multidisciplinary center which, as part of Fujitsu’s global R&D activity, conducts research and innovation – achieving together whilst supporting our employees.


We are currently looking for a researcher in our Computing Research Group, working on exploring how the use High Performance Computing to accelerate applications at the intersection of Artificial Intelligence and Genomics.



Your role will involve:


  • Analyzing and profiling code to find hotspots
  • Using parallel and distributed computing techniques to accelerate algorithms, in particular those dealing with large scale graph computations
  • Optimization for heterogeneous (CPU + GPU) architectures or for Fujitsu’s Arm-based A64FX processor



Your experience


To be suitable for this opportunity, you will be pro-active in your approach, adaptable and able to demonstrate that you have:

  • A PhD or similar Post-Graduate qualification in a relevant field
  • Experience with High Performance Computing techniques such as MPI, OpenMP, Intel TBB etc
  • High proficiency in one or more programming languages
  • A track record of writing academic publications
  • Excellent written and verbal communication skills
  • The following skills are optional but desirable:

· Experience with Graph based algorithms such as Graph Neural Networks

· Working with knowledge graphs and graph databases

· Experience in a healthcare related field such as cell simulation, bio-informatics or genomics



Achieve together


We want the best people on our team, so we welcome and encourage applications from people with a diverse variety of experiences, backgrounds and identities. The role may demand some flexibility to meet business needs, within a culture of respect for professional and private commitments. We are committed to equality of opportunity for all.


#AchieveTogether

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

AI Recruitment Trends 2025 (UK): What Job Seekers Must Know About Today’s Hiring Process

Summary: UK AI hiring has shifted from titles & puzzle rounds to skills, portfolios, evals, safety, governance & measurable business impact. This guide explains what’s changed, what to expect in interviews, and how to prepare—especially for LLM application, MLOps/platform, data science, AI product & safety roles. Who this is for: AI/ML engineers, LLM engineers, data scientists, MLOps/platform engineers, AI product managers, applied researchers & safety/governance specialists targeting roles in the UK.

Why AI Careers in the UK Are Becoming More Multidisciplinary

Artificial intelligence is no longer a single-discipline pursuit. In the UK, employers increasingly want talent that can code and communicate, model and manage risk, experiment and empathise. That shift is reshaping job descriptions, training pathways & career progression. AI is touching regulated sectors, sensitive user journeys & public services — so the work now sits at the crossroads of computer science, law, ethics, psychology, linguistics & design. This isn’t a buzzword-driven change. It’s happening because real systems are deployed in the wild where people have rights, needs, habits & constraints. As models move from lab demos to products that diagnose, advise, detect fraud, personalise education or generate media, teams must align performance with accountability, safety & usability. The UK’s maturing AI ecosystem — from startups to FTSE 100s, consultancies, the public sector & universities — is responding by hiring multidisciplinary teams who can anticipate social impact as confidently as they ship features. Below, we unpack the forces behind this change, spotlight five disciplines now fused with AI roles, show what it means for UK job-seekers & employers, and map practical steps to future-proof your CV.

AI Team Structures Explained: Who Does What in a Modern AI Department

Artificial Intelligence (AI) and Machine Learning (ML) are no longer confined to research labs and tech giants. In the UK, organisations from healthcare and finance to retail and logistics are adopting AI to solve problems, automate processes, and create new products. With this growth comes the need for well-structured teams. But what does an AI department actually look like? Who does what? And how do all the moving parts come together to deliver business value? In this guide, we’ll explain modern AI team structures, break down the responsibilities of each role, explore how teams differ in startups versus enterprises, and highlight what UK employers are looking for. Whether you’re an applicant or an employer, this article will help you understand the anatomy of a successful AI department.