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Work as part of a multi-disciplinary team of computational chemists, medicinal chemists, structural biologists, data scientists, pharmacologists and biologists and provide computational expertise to advance drug discovery projects. Contribute to drug discovery efforts across various modalities including small molecules, PROTACs, RNA inhibitors, peptides, and more. Implement and execute innovative computational methodologies and tools such as AI, free energy, and cheminformatics approaches to support drug discovery efforts.
Job Responsibility
Independently design and execute computational strategies for drug discovery projects
Contribute as a key scientific expert within one or more project teams
Develop and apply innovative computational methodologies to solve project challenges
Influence project decisions through data-driven insights
Mentor junior scientists and contribute to scientific excellence
Provide scientific and strategic leadership across multiple drug discovery projects
Shape computational chemistry strategies and influence portfolio-level decisions
Drive adoption of emerging technologies (e.g., AI/ML, generative chemistry) across projects
Act as a thought leader to project teams and senior stakeholders
Influence cross-functional teams without direct line management authority
Mentor and elevate scientific capabilities across the organization
Requirements
PhD degree in Chemistry or equivalent
Ideally 5+ years of experience in industry (pharma/biotech) drug discovery experience required
Business level Japanese in speaking, writing, and reading
Expertise in a variety of computational tools and methodology including generative chemistry, large-scale virtual screening, molecular dynamics, homology modeling, quantum mechanics, pharmacophore elucidation, data mining, machine learning, cheminformatics and more
Significant industry experiences contributing as a computational chemist on drug discovery projects against several therapeutic areas and a variety of drug discovery targets (GPCRs, Kinases, Ion channel etc.)
Strong impact in progressing discovery projects from hits to clinical leads
Familiarity with organic and synthetic chemistry concepts
Provide project teams with computational strategies to inform, influence, and prioritize designs for potency/selectivity and improve ADME/Tox endpoints
Ability to effectively integrate emerging generative chemistry methods and other modern machine learning and artificial intelligence (AI) applications in small molecule drug discovery
Proficiency with state-of-the-art Computational Chemistry software