Research Scientist – In vitro display, Biologics discovery

Introduction to role:

We are

seeking

a highly motivated Research Scientist, Biologics Discovery – In Vitro Display to support our therapeutic discovery pipeline and contribute to the development of recombinant peptide and

antibodies

discovery platforms.

The role will suit an organised and enthusiastic experimental scientist who can contribute to the design and execution of experiments, analyse and interpret data, and communicate findings clearly. Working collaboratively with colleagues across the Biologics Engineering group and broader project teams, the successful candidate will apply scientific curiosity and sound experimental practice to address biologics discovery challenges.

The role will involve the discovery, isolation, and optimisation of peptides and other biologics for therapeutic programmes using a range of in vitro display platforms, including phage, yeast, mRNA, and ribosome display.

This position offers the opportunity to develop

expertise

in peptide and antibody discovery, contribute to innovative biologics engineering approaches, and build experience within a collaborative, multidisciplinary drug discovery environment.

Education & Experience Requirements:

Graduate level scientist with hands-on laboratory-based experience .

Essential Skills/Experience:

E xperience of

biologics/peptide

hit identification and engineering using display technologies such as

phage, yeast, mRNA, and ribosome display

including library design/generation, and selection campaigns using diverse enrichment strategies

H ands-on experience in molecular biology methods and technologies (e.g., PCR, RT-PCR, cloning (ligation-dependent and independent methods), site-directed mutagenesis, Sanger sequencing/analysis, ideally applied to generation of

peptide/antibody

libraries

Experience with automation to

support

discovery efficiency, reproducibility, and throughput.

Awareness of

AI, machine learning, and/or computational methods to therapeutic discovery in support of hit finding, sequence prioritisation or lead optimisation.

Ability to

apply

protocols, troubleshoot, interpret experimental results/ data

and

m aintain

accurate , high quality and up-to-date experimental records