Assistant Principal Scientist, Computational Chemistry

Location: Cambridge, UK; flexible hybrid work with purposeful in-person collaboration at the Babraham Research Campus.

Company

hirify.global is a global biopharmaceutical company developing treatments for patients with serious and rare diseases.

What you will do

• Serve as the senior technical expert in computational chemistry across multiple small-molecule drug discovery programs, from hit identification through lead optimisation.
• Generate and test scientific hypotheses that influence compound design, project strategy, potency, selectivity, and developability.
• Apply structure-based and physics-based methods, including docking, pose prediction, Molecular Dynamics, free-energy calculations, quantum mechanical methods, and water thermodynamic analysis.
• Use protein structures, cheminformatics, QSAR, ADMET modelling, machine learning, chemical-space analysis, and analogue enumeration to generate actionable insights.
• Collaborate with medicinal chemists, structural biologists, DMPK scientists, and compound profiling teams.
• Develop computational workflows, evaluate emerging methodologies, present complex analyses, and provide informal technical mentoring.

Requirements

• PhD, or MSc with equivalent industrial experience, in Computational Chemistry, Chemistry, Chemical Physics, Biophysics, or a related discipline.
• Typically 8+ years of post-PhD industrial experience applying computational chemistry to small-molecule drug discovery.
• Experience supporting hit identification and lead optimisation across multiple programs.
• Deep expertise in physics-based computational chemistry, medicinal chemistry, structure-based drug design, and predictive modelling.
• Ability to develop computational strategies that influence lead development and optimisation decisions.
• Excellent communication skills and the ability to influence multidisciplinary and senior teams through technical credibility.

Nice to have

• Experience integrating physics-based methods with cheminformatics, machine learning, or AI-driven approaches.
• Experience with Schrödinger or equivalent molecular modelling platforms and open-source tools such as OpenMM.
• Experience with Linux, GPU, HPC, cloud infrastructure, KNIME, or reusable computational workflows.
• Scientific innovation demonstrated through publications, presentations, or successful implementation of new methodologies.
• Experience mentoring scientists and developing computational capabilities in a multidisciplinary research environment.

Culture & Benefits

• Flexible work schedules with purposeful in-person collaboration.
• Brand-new laboratories and offices at the Babraham Research Campus.
• Retirement benefits, global equity awards, and participation in the Employee Stock Purchase Plan.
• Career development through internal and external learning programs, LinkedIn Learning, and role-specific training.
• Hybrid-friendly technology and IT support for collaboration across locations and time zones.
• Global recognition programs and Employee Resource Groups.

Hiring process

• Applications are accepted for five calendar days from the posting date or until the position is filled.