Computational Drug Designer, London

Your impact

As part of our expansion, we are excited to hire talented and motivated Computational Drug Designers. This is a fantastic opportunity for scientists early in their careers to enter the exciting field of AI-driven drug discovery.

You will be an integral part of project teams, learning how to apply the latest AI to drug design. Working alongside experienced medicinal and computational drug designers, as well as machine learning engineers within an interdisciplinary team, you will receive dedicated mentorship and gain hands-on experience applying state-of-the-art computational tools to real-world drug discovery challenges. You will be working within the early stages of drug discovery projects and in highly exploratory projects to develop new chemical starting points. Your contributions will be defining the success of the future portfolio at Iso. If you are ambitious, eager to learn, and want to apply your computational skills in a cutting-edge environment, Isomorphic Labs offers an unparalleled opportunity for growth.

What you will do

• Collaborate with Medicinal Chemistry, Biology, Computational Biology, Machine Learning Engineers in early phase drug discovery projects.
• Contribute to Drug Design: Apply your knowledge on virtual screening approaches, new modalities and novel approaches to target engagement using Iso’s ground-breaking technologies.
• Technology Assessment: Work closely with machine learning engineers in assessing and troubleshooting our latest technology for particular protein targets.
• Data Analysis & Interpretation: Analyse and interpret biological and chemical data using tools such as Python (Pandas/Polars) or KNIME.
• Collaborate Effectively: Work within multi-disciplinary project teams (including medicinal chemists, biologists, DMPK scientists, AI/ML researchers) and manage relationships with external CROs under guidance.
• Communicate Science: Prepare clear summaries, reports, and presentations of your work for internal meetings and potentially contribute to documentation for external partners.
• Learn and Grow: Actively seek, and engage in, learning opportunities, embrace feedback, and contribute positively to our inclusive and science-driven culture.

Skills and qualifications

Essential:

• PhD in computational chemistry, medicinal chemistry, synthetic organic chemistry, or a related technical field, or equivalent experience.
• Strong foundational knowledge of modern computational chemistry.
• Foundational understanding of core computational chemistry concepts (e.g. cheminformatics, virtual screening, docking, machine learning models, model assessment).
• Demonstrated problem-solving skills and scientific curiosity.
• Excellent communication (written and verbal) and interpersonal skills, with an ability to work effectively in a collaborative team environment.
• A genuine passion and enthusiasm for applying AI/ML to drug discovery and how this can transform the field.
• A strong growth mindset, adaptability, and eagerness to learn new concepts and techniques.
• Comfortable working within ambiguous environments and prepared to challenge the way we do drug discovery.

Nice to have:

• 1-5 years of relevant postdoctoral or industrial computational chemistry experience.
• Experience working with or managing activities at Contract Research Organisations (CROs).
• Familiarity with medicinal chemistry techniques (e.g., data analysis software, ADMET principles).
• Knowledge of specific drug discovery approaches like Structure-Based Drug Design (SBDD), Fragment-Based Drug Design (FBDD), and alternative modalities like PROTACs, Molecular Glues, PPI Inhibitors or Stabilisers etc.
• Basic understanding of Drug Metabolism and Pharmacokinetics (DMPK) principles.
• Fluent in Python with ability to write code for new tools.
• Track record of authorship of relevant scientific manuscripts and/or inventorship of composition of matter patents.

Hybrid working
It’s hugely important for us to share knowledge and build strong relationships with each other, and we find it easier to do this if we spend time together in person. This is why we follow a hybrid model, and would require you to be able to come into the office 3 days a week (currently Tuesday, Wednesday, and one other day depending on which team you’re in). If you have additional needs that would prevent you from following this hybrid approach, we’d be happy to talk through these if you’re selected for an initial screening call.