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

Apply Now

Principal computational genetics scientist

Next-Link
Slough
1 year ago
Applications closed

Related Jobs

View all jobs

Data Scientist (TTS)

Data Scientist

Principal Data Scientist

Principal Machine Learning Engineer

Principal Data Scientist

Principal Data Scientist I - Agentic Systems

The Genetics groupis small but dynamic group that develops and applies leading edgeanalytics and approaches to answer a diverse set of questions.Although situated in the Patient Solutions part of the organizationthe group supports the complete R&D pipeline ranging fromtarget identification clinical development and through topostmarketing. The Genetics group supports all the sites andgeographies.
We are looking for a contractor to supportthe analytical workload within the group as well as to be involvedin and potentially lead projects with an outward facing role.


Requirements

Required:
Direct experience of analysing and using genetic data generatedthrough multiple platforms and associated analyticalapproaches.
Expert knowledge of statistics with specific experience in andapplication of statisticalgenetics.
Advanced computational skills: proficiency in using R python SQLbash and experience of working in a cloudenvironment.
Ability to interpret and present data in the context of thequestionunderstudy.
Good knowledge of the drug discoveryprocess.
Problem solvingskills.

Preferred:
Experience of the application of genetics and genetic approaches todrug discovery anddevelopment.
Experience of using and querying populationdatabases.
Expertise in methods for functional interpretation of genomics datasuch as variant and gene pathway mapping andenrichment.
Ability to understand and integrate data from other sources (e.g.transcriptomicsproteomics).
Expertise in the application of machine learning or artificialintelligenceapproaches.
Relevant biologyexpertise.

Behaviours:
Good interpersonalskills.
Ability to work both independently and in a team to deliver againstdeadlines.
Ability to communicate efficiently the outcomes of analytical workto diverseaudiences.
Ability to work and collaborate with colleagues from otherfunctions.
Ability to quickly accumulate new knowledge and the agility to movequickly between diverseprojects.
Excellent communication skills in English and the ability to usethese skills effectively in an international and multiculturalenvironment.


Requirements Required: Direct experience of analysing and usinggenetic data generated through multiple platforms and associatedanalytical approaches. Expert knowledge of statistics with specificexperience in, and application of, statistical genetics. Advancedcomputational skills: proficiency in using R, python, SQL, bash andexperience of working in a cloud environment. Ability to interpretand present data in the context of the question understudy. Goodknowledge of the drug discovery process. Problem solving skills.Preferred: Experience of the application of genetics and geneticapproaches to drug discovery and development. Experience of usingand querying population databases. Expertise in methods forfunctional interpretation of genomics data, such as variant andgene pathway mapping and enrichment. Ability to understand andintegrate data from other sources (e.g. transcriptomics,proteomics). Expertise in the application of machine learning orartificial intelligence approaches. Relevant biology expertise.Behaviours: Good inter-personal skills. Ability to work bothindependently and in a team to deliver against deadlines. Abilityto communicate efficiently the outcomes of analytical work todiverse audiences. Ability to work and collaborate with colleaguesfrom other functions. Ability to quickly accumulate new knowledgeand the agility to move quickly between diverse projects. Excellentcommunication skills in English and the ability to use these skillseffectively in an international and multiculturalenvironment.

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.