AI Protein Design Scientist
1 day ago
City of London
An exciting opportunity has arisen to join a recently funded, early-stage biotechnology company developing a highly ambitious programmable therapeutics platform for oncology. The company is building a new class of target-selective therapeutic systems designed to act only in disease-relevant cellular contexts. At the core of the platform is the design and engineering of proteins whose behaviour can be precisely controlled, using advances in protein structure prediction, generative design, protein language models and experimental validation. Having recently secured seed funding, the company is now expanding its technical team and is looking for a computational protein design scientist to help build the company’s AI-enabled protein engineering capability. This is a rare opportunity to join a fast-moving biotech at an early stage, working directly at the interface of protein design, structural biology, computational modelling and wet-lab validation. Why Join? • Join a recently seed-funded biotech at a pivotal stage of platform and pipeline development, • Help shape the company’s computational protein design strategy from an early stage, • Work on highly novel protein systems where structure, function, activation and selectivity are central to therapeutic performance, • Apply cutting-edge protein structure AI tools to real therapeutic construct design problems, • Translate computational designs into experimentally testable hypotheses and real biological data Job Title: Computational Protein Design Scientist Location: Remote or London, Hybrid Reports to: CTO Salary: Competitive, dependent on experience About the Role As a Computational Protein Design Scientist, you will use AI-enabled protein structure prediction, protein design tools and computational modelling to design, evaluate and optimise engineered therapeutic proteins. This is a highly technical role for someone who is excited by the practical application of modern protein design methods, including tools such as AlphaFold, Boltz, RoseTTAFold, Rosetta, BindCraft, ESM, ProteinMPNN, Protenix and related structure or sequence-based models. You will work closely with construct engineering and biology teams to design novel protein systems, prioritise variants, interpret structural hypotheses and close the loop between computational prediction and experimental validation. You will be responsible for developing and maintaining computational workflows that help the company understand how engineered protein systems may fold, bind, activate, switch or respond to disease-relevant cellular contexts. The focus will be on using computational tools to guide real-world construct design decisions, reduce experimental search space and accelerate the development of programmable therapeutic systems. Key responsibilities will include: • Applying protein structure prediction tools such as AlphaFold, Boltz, RoseTTAFold, Protenix or related models to evaluate engineered protein constructs, • Using computational protein design platforms such as Rosetta, BindCraft, ProteinMPNN, ESM and other emerging tools to design and optimise therapeutic protein systems, • Designing, ranking and prioritising protein variants for experimental testing based on structural, functional and developability considerations, • Building workflows for in silico construct design, structural evaluation, interface design, binder design and protein optimisation, • Working closely with wet-lab, construct engineering and biology teams to translate computational designs into experimentally testable hypotheses, • Interpreting model outputs critically, including confidence metrics, structural plausibility, failure modes and uncertainty, • Supporting the design of engineered activation mechanisms, target-selective systems and controllable protein behaviours, • Integrating computational predictions with experimental data to improve future design cycles, • Developing and maintaining computational pipelines, analysis tools and design infrastructure, • Keeping pace with emerging protein design and structure AI methods, and identifying where they can be applied meaningfully to the company’s platform Desired Qualifications and Experience • PhD or equivalent experience in Computational Protein Design, Structural Biology, Computational Biology, Protein Engineering, Biophysics, Bioinformatics or a closely related field, • Strong hands-on experience using protein structure prediction, design or modelling tools such as AlphaFold, Boltz, RoseTTAFold, Rosetta, BindCraft, ESM, ProteinMPNN, Protenix or similar platforms, • Strong understanding of protein structure, folding, binding, interfaces, conformational change and structure-function relationships, • Experience designing or evaluating engineered proteins, protein binders, enzymes, switches, allosteric systems or multi-domain constructs, • Ability to critically assess computational model outputs, including confidence scores, structural artefacts, hallucinated interactions and likely experimental failure modes, • Strong Python skills and experience building reproducible computational workflows or analysis pipelines, • Familiarity with structural file formats, protein sequence analysis, structure visualisation and common bioinformatics / structural biology tooling, • Track record of translating computational predictions into experimentally testable designs or hypotheses, • Comfortable working in close collaboration with experimental scientists and iterating designs based on wet-lab feedback Preferred Experience • Experience applying generative AI or protein language models to protein design problems, • Experience with binder design, interface design, de novo protein design or scaffold optimisation, • Familiarity with CRISPR/Cas systems, conformational activation mechanisms or programmable biology platforms, • Experience working with high-throughput experimental data to inform protein design cycles, • Experience integrating cryo-EM, X-ray crystallography, AlphaFold models or other structural data into design workflows, • Familiarity with molecular dynamics or biophysical simulation as a complementary tool for evaluating designed constructs, • Experience running computational protein design workflows on cloud or GPU-enabled infrastructure, • Background in oncology, targeted therapeutics, cell-selective systems or synthetic biology, • Comfort operating as an early computational hire within a small, fast-moving team This is an excellent opportunity for a computational protein design scientist to join a recently funded oncology biotech at an early and highly influential stage. You will help shape the company’s computational design capability, apply cutting-edge protein structure AI tools to real therapeutic design challenges, and play a central role in engineering programmable protein systems with the potential to create a new class of targeted oncology therapeutics. To apply, please submit an updated CV for consideration.
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