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Biomedical Scientist jobs in United Kingdom

Modeller and Data Scientist

CEPI (Coalition for Epidemic Preparedness Innovations)

City Of London
On-site
GBP 45,000 - 65,000
29 days ago
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Imaging Biomarker Scientist in Translational Imaging & Data

Perspectum Ltd

Oxford
On-site
GBP 40,000 - 60,000
29 days ago

Locum Band 6 Haematology & Transfusion Scientist

Sanctuary Personnel Ltd

Ashton-under-Lyne
On-site
GBP 60,000 - 80,000
29 days ago

AI Research Associate/Fellow – Digital Cancer Screening

Karlstad University

Nottingham
On-site
GBP 60,000 - 80,000
16 days ago

Research Associate/Fellow (Fixed Term) (MED263625)

Karlstad University

Nottingham
On-site
GBP 60,000 - 80,000
16 days ago
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Cardiovascular Mechanotransduction Research Associate

KINGS COLLEGE LONDON

United Kingdom
On-site
GBP 45,000 - 47,000
16 days ago

Research Associate, School of Cardiovascular & Metabolic Medicine & Sciences

KINGS COLLEGE LONDON

United Kingdom
On-site
GBP 45,000 - 47,000
16 days ago

Scientist Molecular Diagnostics

taylorollinson Ltd

United Kingdom
On-site
GBP 80,000 - 100,000
16 days ago
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NGS Product Development Scientist – Molecular Diagnostics

taylorollinson Ltd

United Kingdom
On-site
GBP 80,000 - 100,000
16 days ago

Analytical Scientist: HPLC Method Development

MedPharm Ltd

Guildford
On-site
GBP 30,000 - 45,000
16 days ago

Associate Scientist, Analytical

MedPharm Ltd

Guildford
On-site
GBP 30,000 - 45,000
16 days ago

Clinical Research Associate in the Department of Psychosis Studies

KINGS COLLEGE LONDON

United Kingdom
On-site
GBP 45,000 - 68,000
16 days ago

Clinical Research Associate: Psychosis Studies & Neuroimaging

KINGS COLLEGE LONDON

United Kingdom
On-site
GBP 45,000 - 68,000
16 days ago

Research Associate/Fellow (Fixed Term) (MED263625)

University of Nottingham

United Kingdom
On-site
GBP 32,000 - 40,000
16 days ago

Research Associate/Fellow - Digital Cancer AI Research

University of Nottingham

United Kingdom
On-site
GBP 32,000 - 40,000
16 days ago

Senior UX Researcher & Team Lead — Hybrid (Remote/Manchester)

LA International

United Kingdom
Hybrid
GBP 80,000 - 100,000
16 days ago

UX Researcher

LA International

United Kingdom
Hybrid
GBP 80,000 - 100,000
16 days ago

Quantitative Research Associate — ML‑Driven Derivatives

JPMorganChase

Greater London
On-site
GBP 65,000 - 85,000
16 days ago

Quantitative Researcher - Rates.

Millennium Management

Greater London
On-site
GBP 80,000 - 100,000
16 days ago

Senior Scientist in Process Analytical Technology (PAT)

AstraZeneca

Macclesfield
On-site
GBP 50,000 - 70,000
16 days ago

Senior Scientist, PAT & Process Control (Advanced Analytics)

AstraZeneca

Macclesfield
On-site
GBP 50,000 - 70,000
16 days ago

Research Associate (Design)

Manchester Metropolitan University

Manchester
Hybrid
GBP 30,000 - 38,000
16 days ago

Remote Interim User Researcher (8-week contract)

Public Sector Resourcing

England
Remote
GBP 60,000 - 80,000
16 days ago

Interim User Researcher

Public Sector Resourcing

England
Remote
GBP 60,000 - 80,000
16 days ago

Wastewater Process Scientist: Impact & Compliance Lead

Anglian Water Services

Ely
Hybrid
GBP 41,000 - 48,000
16 days ago

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Modeller and Data Scientist
CEPI (Coalition for Epidemic Preparedness Innovations)
City Of London
On-site
GBP 45,000 - 65,000
Full time
29 days ago

Job summary

A global health organization based in London is seeking a Modeller and Data Scientist for a 12-month full-time fixed-term contract. The role involves advanced data analysis techniques to support vaccine development and preparedness against outbreaks. Candidates should possess an MSc or PhD in a related field and at least three years of experience. Strong skills in R and Git are essential, with familiarity in Python being preferred. The position offers an inclusive environment and the chance to work on significant global health challenges.

Benefits

Opportunity to work with leading experts
Experience in vaccine development
Diverse and inclusive working environment

Qualifications

  • Strong quantitative background with an advanced degree.
  • At least three years of relevant experience.
  • Experience in outbreak analytics or epidemiological forecasting.

Responsibilities

  • Prepare and clean datasets for modelling.
  • Define quantitative thresholds for outbreak response.
  • Run validated model templates and provide timely outputs.

Skills

Applied quantitative analysis
Statistical methods
Mathematical modelling
Introductory machine learning
R
Git and GitHub

Education

MSc in data science, mathematical modelling, infectious disease epidemiology, computer science, biostatistics
PhD (newly qualified)

Tools

Python
Job description

Organisation CEPI (Coalition for Epidemic Preparedness Innovations) Locations: London, UK

Application Deadline: 38 days remaining

The Coalition for Epidemic Preparedness Innovations (CEPI) is an international coalition of governments, academic, philanthropic, private, public, and intergovernmental institutions whose vision is to create a world in which epidemics and pandemics are no longer a threat to humanity. CEPI played a central role in the global response to COVID‑19 and has contributed to a number of scientific breakthroughs in vaccine development against other infectious diseases, including the first ever licensed Chikungunya vaccine and the first Nipah and Lassa virus vaccines into Phase 1 trials. Central to CEPI’s five‑year plan known as CEPI 2.0 is CEPI’s goal to accelerate the time taken to develop safe, effective, globally accessible vaccines against new threats to just 100 days. Achieving this ‘100 Days Mission’, which has been embraced by the G7 and G20.

CEPI is a not‑for‑profit association under Norwegian Law and has offices in Oslo (HQ), London, and Washington DC.

In CEPI we strive for diverse thinking, and we want a diverse pool of candidates for all our vacancies. We work for an inclusive working environment where each employee can contribute and grow.

More details about CEPI and our mission can be found on our website: www.cepi.net

About the role

CEPI is seeking a skilled Modeller and Data Scientist to join our team for a 12‑month full‑time fixed‑term contract. The candidate will have expertise in various data analysis techniques (e.g., mathematical, statistical, epidemiological), infectious diseases and emerging pathogens. The role will be part of the Epidemiology and Data Sciences (E&DS) department within the R&D division. The E&DS department supports CEPI, its partners and stakeholders by bridging key epidemiological knowledge gaps to advance vaccine development, strengthen outbreak preparedness, and support achievement of CEPI’s 100 Days Mission.

The role strengthens CEPI’s in‑house analytical capacity and supports delivery of the Data Science and Advanced Analysis strategy. It provides core modelling and data support needed to advance CEPI’s vaccine candidate portfolio for priority pathogens and to contribute to CEPI’s preparedness and emergency response plans. The postholder will help maintain in‑house rapid‑response modelling capability, ensure continuity of evidence generation to support vaccine R&D, and reinforce CEPI’s global partnerships. The role requires someone who is proactive, self‑sufficient, and able to work effectively within a cross‑functional team as well as independently.

We are looking for candidates who bring a strong quantitative background with an advanced degree (MSc or newly qualified PhD) in data science, mathematical modelling, infectious disease epidemiology, computer science, biostatistics or a closely related field. They should have at least three years of relevant experience and be prepared to work in a matrixed, cross‑functional environment. The ideal candidate will have solid skills in applied quantitative analysis, including statistical methods, mathematical modelling, and introductory machine learning, and experience in outbreak analytics or epidemiological forecasting. Competency in R alongside Git and Github is essential, with either working knowledge of Python or a clear willingness to learn.

The post‑holder will report directly to the Head of Data Science and Advanced Analysis and work closely with members of the team as well as collaborate across the Epidemiology and Data Science department.

Responsibilities
  • Prepare and clean surveillance, genomic, and outbreak datasets early, using best judgement to anticipate what will be needed for modelling. This includes running preliminary analyses or engaging relevant country modellers ahead of formal requests.
  • With departmental input, define quantitative thresholds for triggering CEPI’s outbreak response
  • Maintain version control and documentation for CEPI’s model repository, ensuring workflows remain up to date and ready for rapid activation.
  • Run validated and documented model templates under supervision and provide timely outputs that support outbreak forecasts, scenario analysis, and rapid risk assessments
  • Contribute to the design, execution, and reporting of simulation exercises by proactively identifying gaps, making improvements, and providing required inputs.
  • Summarise model outputs for internal briefs, dashboards, and decision documents, and surface key insights without waiting for prompts.
Knowledge and Evidence Generation
  • Compile disease burden, stockpile, and vaccine‑impact data for forecasting, portfolio planning, and CEPI’s 100 Days Mission metrics.
  • Conduct basic statistical analyses and produce clear visual outputs in R or Python.
  • Support the development, testing, and documentation of AI and predictive modelling pipelines.
  • Contribute to evidence summaries, technical notes, and rapid analyses for R&D (i.e., RDP, Clinical Development, Regulatory) and other internal stakeholders.
  • Provide analytical and coordination support to CEPI’s modelling network and regional modelling partners including Africa CDC, PAHO, ICMR, and other networks.
  • Prepare partner data templates, manage collaborative workspaces, and ensure quality control of shared datasets.
  • Track outputs from regional outbreak modelling exercises and consolidate lessons learned.
  • Support monitoring and evaluation for modelling partnerships.
  • Contribute to external engagement through slide preparation, meeting coordination, and drafting policy briefs.
  • Help strengthen the visibility of CEPI’s modelling partnerships and connect internal teams with regional networks.
Cross‑Functional and Internal Support
  • Support delivery of the DSAA and E&DS strategy with analytical inputs and operational support.
  • Provide disease‑specific analyses for priority pathogens including Lassa, Chikungunya, H5N1, RVF, SARS‑CoV‑2, and novel pathogens.
  • Support CEPI’s supply‑chain and vaccine deployment modelling initiatives.
  • Assist with CEPI’s climate‑health analytical work, where relevant.
  • Participate in internal emergency response structures and provide modelling support when required.
  • Contribute to internal and external workshops designed to strengthen predictive modelling capacity and shape future DSAA plans.
  • Perform other duties that support the smooth functioning of the DSAA work programme.
  • Represent CEPI in external scientific and technical discussions with partners and stakeholders.
  • Provide modelling and operational support to senior DSAA team members when required.
  • Provide statistical support to study design and analyses to the wider department, including input into observational and RWE studies when required.
Education, Experience and Competence
  • MSc or recent PhD in data science, modelling, epidemiology, computer science, biostatistics, or a related quantitative field.
  • 1‑3 years’ experience in outbreak analytics, epidemic forecasting, or epidemiological modelling.
  • Proficient in R, Git, and GitHub; working knowledge of Python or willingness to learn.
  • Proven ability to manage multiple tasks at pace with strong organisational and time‑management skills.
  • Experience providing decision‑ready analyses to public health or research settings.
  • Strong written and verbal communication skills, with the ability to translate technical concepts for non‑technical audiences.
  • Understanding of infectious disease transmission, vaccine‑impact modelling, and global preparedness needs.
  • Awareness of AI/ML applications in biomedical or epidemiological domains.
  • Ability to collaborate effectively across geographic regions and disciplines.
  • High degree of initiative, problem‑solving ability, and adaptability.
  • Experience working in matrixed cross‑functional teams.
  • Familiarity with vaccine stockpile and demand modelling.
  • Understanding of data sharing challenges, model validation needs, and responsible AI considerations.
  • Experience with climate‑health interactions or One Health approaches.
  • Previous work within emergency response, rapid risk assessment, or operational public health analytics.
Travel and Location Requirements
  • This position must be based in London, UK or Oslo, Norway.
  • Relocation assistance and work visa sponsorship are not available for this fixed‑term position.
  • International travel up to 10%.
What we can offer you
  • The opportunity to work together with leading experts on solutions for global challenges
  • Experience in the international effort on developing vaccines against emerging infectious diseases and accelerating vaccine development response to outbreaks
  • A diverse and inclusive working environment
How to apply
  • For more information on how to apply, please visit: https://cepisites.secure.force.com/careers
  • Should you have any issues submitting your application or have questions please contact jobs@cepi.net
  • Background verification will be conducted to verify information provided in the CV and available documentation.
  • Deadline for receiving applications is 4th January 2026 at 23:59 CET

CEPI (Coalition for Epidemic Preparedness Innovations)

London EC2R 7HJ, Salford M50 3SP, Staines TW18 3DZ

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* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.

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