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Structure Therapeutics develops life‐changing medicines for patients using advanced structure‐based and computational drug discovery technology. The company’s platform combines the latest advancements in visualization of molecular interactions, computational chemistry, and data integration to design orally available, superior small molecule medicines that overcome current limitations of biologic and peptide drugs. We are advancing a clinical‐stage pipeline of differentiated treatments focused on chronic diseases with high unmet need, including cardiovascular, metabolic, and pulmonary conditions.

Structure Therapeutics is led by an experienced group of international drug innovators and financed by top-tier global life sciences investors. The company has completed an initial public offering (IPO) in February of 2023. With offices in California and Shanghai, Structure Therapeutics has the benefit of being at the center of life science innovation in both the US and China and capitalizing on the strengths of each geographic location.

LOCATION & DURATION

All internships will be based in Shanghai office. This internship starts in June 2025 for approximately 10-12 weeks. This is a full-time (40 hours per week) paid internship.

POSITION SUMMARY

· We are seeking a motivated and detail-oriented Summer Intern to support our research and development in the customization and application of Large Language Models (LLMs) for chemogenomics-scale protein-ligand bioactivity prediction/Or Co-folding algorithms for structure prediction of protein-ligand complexes.
This internship offers a hands-on opportunity to work with cutting-edge open-source tools. The ideal candidate will have a strong background in Python programming and a keen interest in cheminformatics, computational chemistry, and computer-aided drug discovery.

ESSENTIAL DUTIES AND RESPONSIBILITIES

· Deploy and configure open-source Large Language Model packages and public chemogenomics resources

· Deploy and configure open-source co-folding algorithm packages

· Benchmark and evaluate algorithm performance using curated datasets of protein-ligand bioactivity data

· Document experimental setups, configurations, and outcomes

· Analyze and interpret results to support model comparisons

· Collaborate with team members to share findings and improve workflows

· Assist with troubleshooting and optimizing deployment pipelines

REQUIREMENTS

· Strong programming skills in Python

· Familiarity with protein structure prediction and co-folding algorithms

· Experience working with Linux-based systems and command-line tools

· Ability to work independently and manage time effectively

· Strong analytical thinking and attention to detail

· Background in cheminformatics, computational chemistry, or a related discipline

· A full-time student in an accredited program with plans to return to school in the fall

· All applicants must be at least 18 years of age by June 1, 2025.