Principal Computational Chemist Job at Life Science Talent (København)

Job Description

Join our Computational Drug Design Team to play a key role in the development and application of Orbis Medicines’ next-generation nCycle platform. Orbis Medicines is a pioneering Biotech company powered by our automated nGen chemistry platform and data-driven approach. We develop oral alternatives to injectable biologics and design drugs for hard-to-drug targets primarily in inflammation and immune-driven diseases. Orbis’ nGen platform designs macrocycles with oral bioavailability (nCycles) by combining AI technologies with automated synthesis and high-throughput screening of real compounds. We are seeking a Principal Computational Chemist to lead our efforts to uncover new nCycles for difficult-to-drug targets and shape our structure-based design strategy for macrocyclic peptide programs. This is a senior scientific leadership role with direct impact on the development of our macrocyclic peptide platform.

Job Responsibility

Define and lead the structure-based design strategy across macrocyclic peptide programs, aligning computational approaches with our platform goals
Drive macrocycle hit identification by applying structural modelling, co-folding and conformational analysis to prioritize molecules for synthesis and experimental testing
Guide approaches to address macrocyclic peptide flexibility, cell permeability prediction, and binding mode assessment
Integrate experimental structural data (X-ray, cryo-EM and NMR) with predictive models and molecular modeling tools to inform design hypotheses and accelerate design cycles
Communicate complex computational findings clearly to multidisciplinary stakeholders, translating analyses into actionable recommendations
Collaborate with machine learning colleagues to develop and deploy next-generation modelling and design tools that enhance nCycle program productivity
Partner closely with peptide chemists and biologists to drive data-informed macrocyclic library design and interpret experimental results
Represent the computational strategy in internal and external scientific discussions, contributing to project reviews, collaborations and publications

Requirements

MSc or PhD in Computational Chemistry, Structural Biology, Chemistry or a related discipline, with a strong grounding in molecular modelling and drug discovery
Demonstrated experience applying structure-based drug design in an industrial or biotech setting to progress programs from hit finding through optimisation
Strong proficiency in Python and the ability to build, maintain and automate robust computational workflows for analysis and design
Willingness to provide high-impact scientific leadership across multiple projects and independently champion modeling strategies that drive critical project decisions

Nice to have

Experience working with macrocycles and/or peptide therapeutics, including considerations of conformational behaviour and permeability
Experience applying co-folding or structure-prediction methodologies in drug discovery, using them to guide design decisions and prioritisation
Experience with Molecular Design products such as Schrodinger Suite, MOE, Cresset
experience with Molecular Modeling tools such as OpenMM, Gromacs or Rosetta

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Principal Computational Chemist

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