National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Antibody Discovery and Engineering Scientist

Britwell
2 weeks ago
Create job alert

Do you want to help shape the delivery of next generation antibody therapeutics? Do you have knowledge of molecular biology and microbiological methods, and a proven track record of antibody discovery or protein engineering? If so, we would love to hear from you!

We are recruiting for an Antibody Discovery and Engineering Scientist, at either Senior or Research Scientist level. This role is offered on a contract basis initially for 12 months.

This is an excellent opportunity to join a dynamic and thriving team of scientists helping to develop and validate new sequence-based and structure-based antibody design approaches. This includes elements of antibody hit identification, sequence optimisation and in silico de novo antibody design.

Responsibilities:

Play a key role in the discovery of therapeutic monoclonal antibodies to support our clients pipeline and help create value for patients suffering with serious disease
Using cutting-edge yeast display for the discovery and optimisation of human antibodies aligned with therapeutic targets
Design, construct, and perform selections using bespoke synthetic display libraries to support in silico de novo antibody discovery and optimisation projects
The preparation of next generation sequencing (NGS) libraries and their analyses to support antibody discovery and engineering of lead molecules
Working closely with computational and CADD scientists, co-develop and apply AI/Deep learning solutions and structure-based approaches to facilitate discovery and engineering of high-quality antibody molecules
Contribute to the development and implementation of new methodologies in antibody display and engineering
Work flexibly across project teams to ensure delivery of results against expected timelines
Present experimental data at cross-functional meetingsQualifications / Experience:

A PhD (or equivalent) with molecular biology and protein biochemistry knowledge ideally within the antibody space
Knowledge and experience in the use of in vitro display libraries for either discovery, affinity maturation, or other protein engineering, preferably to include structure or deep sequence-guided insight would be desirable
Demonstrable experience of biochemical techniques for the characterisation of macromolecules such as flow-cytometry, surface plasmon resonance or Bio-layer interferometry would be beneficial
Skills in informatics and other computational platforms such as molecular visualisation and next generation sequencing data analysis would be advantageous
Highly motivated with excellent attention to detail and critical data analysis skills
A trusted ability to deliver to deadlines
Excellent communication skillsIn 2025, this site will relocate from Slough to Windlesham Surrey so applicants must be able to get to both locations.

Randstad CPE values diversity and promotes equality. No terminology in this advert is intended to discriminate against any of the protected characteristics that fall under the Equality Act 2010. We encourage and welcome applications from all sections of society and are more than happy to discuss reasonable adjustments and/or additional arrangements as required to support your application.

Candidates must be eligible to live and work in the UK.

For the purposes of the Conduct Regulations 2003, when advertising permanent vacancies we are acting as an Employment Agency, and when advertising temporary/contract vacancies we are acting as an Employment Business

Related Jobs

View all jobs

Antibody Discovery and Engineering Scientist

National AI Awards 2025

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.

LinkedIn Profile Checklist for Machine Learning Jobs: 10 Tweaks to Drive Recruiter Interest

The machine learning landscape is rapidly evolving, with demand soaring for experts in modelling, algorithm tuning and data-driven insights. Recruiters hunt for candidates proficient in Python, TensorFlow, PyTorch and MLOps processes. A generic profile simply won’t cut it. Our step-by-step LinkedIn for machine learning jobs checklist covers 10 targeted tweaks to ensure your profile ranks in searches and communicates your technical impact. Whether launching your ML career or seeking leadership roles, these optimisations will sharpen your professional narrative and boost recruiter engagement.

Part-Time Study Routes That Lead to Machine Learning Jobs: Evening Courses, Bootcamps & Online Masters

Machine learning—a subset of artificial intelligence—enables computers to learn from data and improve over time without explicit programming. From predictive maintenance in manufacturing to recommendation engines in e-commerce and diagnostic tools in healthcare, machine learning (ML) underpins many of today’s most innovative applications. In the UK, demand for ML professionals—engineers, data scientists, research scientists and ML operations specialists—is growing rapidly, with roles projected to increase by over 50% in the next five years. However, many aspiring ML practitioners cannot step away from work or personal commitments for full-time study. Thankfully, a rich ecosystem of part-time learning pathways—Evening Courses, Intensive Bootcamps and Flexible Online Master’s Programmes—empowers you to learn machine learning while working. This comprehensive guide examines each route: foundational CPD units, immersive bootcamps, accredited online MSc programmes, funding options, planning strategies and a real-world case study. Whether you’re a software developer branching into ML, a statistician aiming to upskill, or a professional exploring AI-driven innovation, you’ll discover how to build in-demand ML expertise on your own schedule.

The Ultimate Assessment-Centre Survival Guide for Machine Learning Jobs in the UK

Assessment centres for machine learning positions in the UK are designed to reflect the complexity and collaboration required in real-world ML projects. From psychometric assessments and live model-building tasks to group data science challenges and behavioural interviews, recruiters evaluate your statistical understanding, coding skills, communication and teamwork. Whether you specialise in deep learning, reinforcement learning or NLP, this guide offers a step-by-step approach to excel at every stage and secure your next ML role.