Antibody Discovery and Engineering Scientist

Slough
11 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.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.