Principal Computational Methodologist (UK)

UCB
Location
Slough, Berkshire
Job Type
Full-time
Posted
July 15, 2026
Views
5

Job Description

Make your mark for patients

We are looking for aPrincipal Computational Methodologistwho is curious, collaborative, and impact-driven to join ourAdvanced Methods and Data Scienceteam within Biometrics and Data Science, based in any of our Brussels (Belgium), Slough (UK) or Raleigh (US).

About the role

You will help shape how advanced AI, machine learning, and computational methods support clinical development. You will design, validate, and deploy models that help teams make evidence-based decisions in areas such as biomarker discovery, clinical trial design, operational efficiency, and patient experience. You will guide scientific thinking, turn complex methods into practical solutions, and help build scalable tools that meet scientific, technical, and regulatory expectations.

Who you will work with

You will join Advanced Methods and Data Science, part of Biometrics and Data Science within Patient Evidence. You will work with clinical, statistical, molecular, operational, engineering, IT, governance, and compliance colleagues across countries. You will also connect with academic, technology, and industry partners. Together, you will explore new methods, share scientific learning, and support teams that use data to improve decision-making across the drug development value chain.

What you will do

  • You will lead AI and machine learning projects that address clinical development, biomarker, operational, and decision-support needs.
  • You will design, build, test, and refine modern deep learning models for text, graphs, biological sequences, and clinical data.
  • You will develop generative AI applications using foundation models, pre-trained models, and large language models.
  • You will run rigorous, reproducible AI experiments on internal and public datasets to generate publishable scientific results.
  • You will partner with engineering teams to package methods into applications, platforms, and scalable validated solutions.
  • You will mentor colleagues, share knowledge, and represent the team through publications, presentations, and external collaborations.

Interested? For this role, we are looking for the following education, experience, and skills:

  • You have a PhD in Statistics, Computer Science, Engineering, Computational Biology, Statistical Genetics, Mathematics, or a related scientific field.
  • You bring experience in industry, ideally within pharma, clinical development, life sciences, or another regulated data-focused environment.
  • You can program confidently in Python, R, or similar languages, and you can support others with practical coding guidance.
  • You understand supervised, unsupervised, Bayesian, and deep learning methods, and can apply them to real-world scientific questions.
  • You have experience with ML infrastructure, reproducible research, Linux or HPC environments, and software or platform development.
  • You communicate clearly with scientific, technical, medical, and business partners, and enjoy working in a collaborative, multidisciplinary team.

Are you ready to ‘go beyond’ to create value and make your mark for patients? If this sounds like you, then we would love to hear from you!

About us
UCB is a global biopharmaceutical company, focusing on neurology and immunology. We are over 9.000 people in all four corners of the globe, inspired by patients and driven by science.

Why work with us?
At UCB, we don’t just complete tasks, we create value. We aren’t afraid to push forward, collaborate, and innovate to make our mark for patients. We have a caring, supportive culture where everyone feels included, respected, and has equal opportunities to do their best work. We ‘go beyond’ to create value for our patients, and always with a human focus, whether that’s on our patients, our employees, or our planet. Working for us, you will discover a place where you can grow, and have the freedom to carve your own career path to achieve your full potential.

At UCB, we’ve embraced a hybrid-first approach to work, bringing teams together in local hubs to foster collaborative curiosity. Unless expressly stated in the description or precluded by the nature of the position, roles are hybrid with 40% of your time spent in the office.

Make your mark for patients

We are looking for aPrincipal Computational Methodologistwho is curious, collaborative, and impact-driven to join ourAdvanced Methods and Data Scienceteam within Biometrics and Data Science, based in any of our Brussels (Belgium), Slough (UK) or Raleigh (US).

About the role

You will help shape how advanced AI, machine learning, and computational methods support clinical development. You will design, validate, and deploy models that help teams make evidence-based decisions in areas such as biomarker discovery, clinical trial design, operational efficiency, and patient experience. You will guide scientific thinking, turn complex methods into practical solutions, and help build scalable tools that meet scientific, technical, and regulatory expectations.

Who you will work with

You will join Advanced Methods and Data Science, part of Biometrics and Data Science within Patient Evidence. You will work with clinical, statistical, molecular, operational, engineering, IT, governance, and compliance colleagues across countries. You will also connect with academic, technology, and industry partners. Together, you will explore new methods, share scientific learning, and support teams that use data to improve decision-making across the drug development value chain.

What you will do

  • You will lead AI and machine learning projects that address clinical development, biomarker, operational, and decision-support needs.
  • You will design, build, test, and refine modern deep learning models for text, graphs, biological sequences, and clinical data.
  • You will develop generative AI applications using foundation models, pre-trained models, and large language models.
  • You will run rigorous, reproducible AI experiments on internal and public datasets to generate publishable scientific results.
  • You will partner with engineering teams to package methods into applications, platforms, and scalable validated solutions.
  • You will mentor colleagues, share knowledge, and represent the team through publications, presentations, and external collaborations.

Interested? For this role, we are looking for the following education, experience, and skills:

  • You have a PhD in Statistics, Computer Science, Engineering, Computational Biology, Statistical Genetics, Mathematics, or a related scientific field.
  • You bring experience in industry, ideally within pharma, clinical development, life sciences, or another regulated data-focused environment.
  • You can program confidently in Python, R, or similar languages, and you can support others with practical coding guidance.
  • You understand supervised, unsupervised, Bayesian, and deep learning methods, and can apply them to real-world scientific questions.
  • You have experience with ML infrastructure, reproducible research, Linux or HPC environments, and software or platform development.
  • You communicate clearly with scientific, technical, medical, and business partners, and enjoy working in a collaborative, multidisciplinary team.

Are you ready to ‘go beyond’ to create value and make your mark for patients? If this sounds like you, then we would love to hear from you!

About us
UCB is a global biopharmaceutical company, focusing on neurology and immunology. We are over 9.000 people in all four corners of the globe, inspired by patients and driven by science.

Why work with us?
At UCB, we don’t just complete tasks, we create value. We aren’t afraid to push forward, collaborate, and innovate to make our mark for patients. We have a caring, supportive culture where everyone feels included, respected, and has equal opportunities to do their best work. We ‘go beyond’ to create value for our patients, and always with a human focus, whether that’s on our patients, our employees, or our planet. Working for us, you will discover a place where you can grow, and have the freedom to carve your own career path to achieve your full potential.

At UCB, we’ve embraced a hybrid-first approach to work, bringing teams together in local hubs to foster collaborative curiosity. Unless expressly stated in the description or precluded by the nature of the position, roles are hybrid with 40% of your time spent in the office.

UCB is an equal opportunity employer. All employment decisions will be made without regard to any characteristic protected by applicable laws.

Should you require any adjustments to our process to assist you in demonstrating your strengths and capabilities contact us on EMEA-Reasonable_Accommodation@ucb.com. Please note should your enquiry not relate to adjustments; we will not be able to support you through this channel.

Frequently Asked Questions

Where is the job located, and is it remote/hybrid/on-site?
The job is located in Slough, Berkshire (UK). UCB operates on a hybrid-first approach, meaning this role is hybrid with 40% of your time spent in the office, unless otherwise stated.
What are the required qualifications and experience for this role?
You need a PhD in Statistics, Computer Science, Engineering, Computational Biology, Statistical Genetics, Mathematics, or a related field. You must have industry experience (ideally in pharma or life sciences), confident programming skills in Python or R, and experience with ML infrastructure, deep learning methods, and software development.
What are the key responsibilities of the Principal Computational Methodologist?
You will lead AI and machine learning projects, design and test deep learning models, and develop generative AI applications. Additionally, you will run reproducible AI experiments, partner with engineering teams to package methods into scalable solutions, and mentor colleagues.
Which team will I be working with?
You will join the Advanced Methods and Data Science team, which is part of Biometrics and Data Science within Patient Evidence. You will collaborate with clinical, statistical, molecular, engineering, and IT colleagues, as well as external academic and industry partners.

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Job Information

Source: manual
AI Relevance: 88/100 (Highly relevant)
Remote Type: onsite
Allowed Locations: Worldwide
Skills & Tags:
ucb machine learning deep learning computational biology statistical genetics data science immunology clinical

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