Join Iambic Therapeutics as a Computational Chemist to drive drug discovery using advanced computational techniques in a collaborative environment.
Posted by employer 2 months ago
First seen on Joblaze 2 months ago
Last verified on the company career page 1 day ago
Skills & Technologies
AI in the day-to-day
Integrate SBDD methods with proprietary transformer-based property prediction technology.
Requirements
Not disclosed in this posting: compensation, visa sponsorship.
Benefits
Joblaze summary
In this role, the Research Scientist II/Senior in Computational Chemistry will focus on applying advanced ligand and structure-based techniques to support drug discovery initiatives. Key skills include proficiency in Python, experience with molecular modeling platforms, and a solid understanding of the drug discovery process. This position is ideal for candidates with a PhD and at least two years of relevant experience, particularly those who thrive in collaborative, cross-functional environments. Iambic Therapeutics, a clinical-stage company, emphasizes innovation through AI-driven methodologies and values diversity within its team.
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Quick facts
From the original posting
JOB SUMMARY
We are seeking a skilled and highly motivated Computational Chemist to join our Computational Sciences group at Iambic Therapeutics. You will be a key player in the application of advanced ligand and structure-based techniques to drive our drug discovery efforts. You will play an active role in the research teams pursuing important therapeutics across multiple indications. You will work in a cross-functional team, collaborating closely with machine learning scientists, medicinal chemists and biologists to apply cutting edge SBDD methods across hit identification, lead optimization, and candidate selection phases. This is a hands-on role, requiring technical expertise in computational chemistry, experience with or strong interest in applying modern co-folding approaches, familiarity with the drug discovery process and a proactive drug-hunter mindset. This role will involve engagement in external partnerships.
This position will be based in our San Diego Headquarters, with exceptions for outstanding candidates to work remotely.
KEY RESPONSIBILITIES
Apply a range of ligand and structure-based approaches across hit identification, hit to lead and lead optimization phases (e.g. cheminformatics, pharmacophore modeling, docking and shape-based based virtual screening, de novo molecular design, MD simulation)
Guide design cycles through the identification of structure-activity relationships and the integration of computational predictions with bioactivity data
Partner with medicinal chemists to design, evaluate and prioritize virtual libraries, and propose actionable molecular designs
Partner with ML scientists to integrate SBDD methods with our proprietary transformer-based property prediction technology (Enchant)
Leverage and evolve our proprietary protein-ligand co-folding technology (NeuralPLexer) to yield novel and actionable structural hypotheses
Translate scientific questions into computational workflows and deliver actionable results
Present results to internal project teams and external partners, explaining methods, implications and recommendations
Develop, validate, and maintain computational workflows and tools
QUALIFICATIONS
Required:
PhD or equivalent degree in computational chemistry (or related field) with 2+ years of relevant experience in drug discovery
Experience supporting active small molecule drug discovery programs
Experience with ligand and structure based design tools
Proficiency in Python for scientific computing, data analysis, and computational workflow development
Excellent written and verbal communication skills; must be able to articulate complex scientific concepts, technical challenges, and results clearly and concisely to diverse audiences.
Strongly preferred:
Industry experience supporting active drug discovery programs
Experience with molecular modeling platforms such as MOE, Schrödinger, OpenEye, or equivalent tools
Familiarity with MD simulation, molecular docking and advanced binding affinity prediction methods (e.g. MM/GBSA, FEP)
Experience with ML-augmented small molecule discovery
ABOUT IAMBIC THERAPEUTICS
MISSION & CORE VALUES
PAY AND BENEFITS
Standard company text repeated across Iambic Therapeutics's postings is omitted here.