Antibody Discovery and Engineering Scientist

Slough
10 months ago
Applications closed

Job Title: Antibody Discovery and Engineering Scientist - Global Biopharmaceutical

Contract: 12-month contract

Location: Slough

Salary: £28.53 PAYE/£38.84 Umbrella

SRG are working with a Global Biopharmaceutical company to help them find a Antibody Discovery and Engineering Scientist to join their busy team.

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. This is a laboratory-based role where a detailed knowledge of molecular biology and microbiological methods, and a proven track record of antibody discovery or protein engineering would be a significant advantage.

Key Responsibilities will include:

Play a key role in the discovery of therapeutic monoclonal antibodies to support the 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 meetings

Candidate Requirements:

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 informatic 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 skills.

Carbon60, Lorien & SRG - The Impellam Group STEM Portfolio are acting as an Employment Business in relation to this vacancy

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.

Jobs

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

Education Jobs

Maths for Machine Learning Jobs: The Only Topics You Actually Need (& How to Learn Them)

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.

Jobs

Neurodiversity in Machine Learning Careers: Turning Different Thinking into a Superpower

Machine learning is about more than just models & metrics. It’s about spotting patterns others miss, asking better questions, challenging assumptions & building systems that work reliably in the real world. That makes it a natural home for many neurodivergent people. If you live with ADHD, autism or dyslexia, you may have been told your brain is “too distracted”, “too literal” or “too disorganised” for a technical career. In reality, many of the traits that can make school or traditional offices hard are exactly the traits that make for excellent ML engineers, applied scientists & MLOps specialists. This guide is written for neurodivergent ML job seekers in the UK. We’ll explore: What neurodiversity means in a machine learning context How ADHD, autism & dyslexia strengths map to ML roles Practical workplace adjustments you can ask for under UK law How to talk about neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in ML – & how to turn “different thinking” into a genuine career advantage.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.