Summer Intern, AI & Computational Chemistry (Discovery Chemistry)

Arrowhead Pharmaceuticals•San Diego, CA

4h•Onsite

About The Position

Arrowhead Pharmaceuticals, Inc. (Nasdaq: ARWR) is a clinical stage biopharmaceutical company that develops medicines that treat intractable diseases by silencing the genes that cause them. Using a broad portfolio of RNA chemistries and efficient modes of delivery, Arrowhead therapies trigger the RNA interference mechanism to induce rapid, deep, and durable knockdown of target genes. RNA interference, or RNAi, is a mechanism present in living cells that inhibits the expression of a specific gene, thereby affecting the production of a specific protein. Arrowhead’s RNAi-based therapeutics leverage this natural pathway of gene silencing. Arrowhead is focused on developing innovative drugs for diseases with a genetic basis, typically characterized by the overproduction of one or more proteins that are involved with disease. The depth and versatility of our RNAi technologies enables us to potentially address conditions in virtually any therapeutic area and pursue disease targets that are not otherwise addressable by small molecules and biologics. Arrowhead is leading the field in bringing the promise of RNAi to address diseases outside of the liver, and our clinical pipeline includes disease targets in the liver and lung with a promising pipeline of preclinical candidates. Arrowhead’s corporate headquarters is in Pasadena, CA with research and development teams in Madison, WI & San Diego, CA, and a state of the art manufacturing facility in Verona, WI. Our employees are nimble, science-driven innovators who are collaborating to bring new therapies to patients in need. The AI & Computational Chemistry Intern will support discovery research at Arrowhead Pharmaceuticals by contributing to an AI-driven virtual compound library initiative. This internship offers hands-on experience working at the intersection of computational chemistry, cheminformatics, and machine learning to support early-stage drug discovery. The intern will play a meaningful role by executing focused technical tasks, improving computational workflows, and supporting model development, helping accelerate project timelines and enhance data quality across the discovery organization. This is an 11-week Summer Internship Program paying $24.00 per hour and requires full-time, onsite work five days per week at the designated location.

Requirements

Currently pursuing a Bachelor’s degree in Computational Chemistry, Chemistry, Bioinformatics, Computer Science, Data Science, or a related technical field.
Basic proficiency in Python and familiarity with scientific or data-processing libraries (e.g., NumPy, pandas, RDKit, PyTorch, TensorFlow).
Fundamental understanding of molecular structures, chemical representations, or machine learning concepts.
Strong problem-solving skills and ability to work independently within established computational workflows.
Excellent verbal and written communication skills.

Nice To Haves

Hands-on experience with Linux environments, shell scripting, or GPU computing.
Prior research or project experience in AI, drug discovery, computational modeling, or molecular biology.
Familiarity with deep learning frameworks or cheminformatics toolkits.
Strong curiosity and motivation to learn at the interface of AI, chemistry, and biology.
Interest in pursuing a career in computational drug discovery or data-driven research.

Responsibilities

Curate, clean, and preprocess molecular and structural datasets to support AI model development and evaluation.
Contribute to algorithm prototyping, benchmarking, and computational experiments related to virtual compound library generation.
Help automate repetitive computational tasks using Python or related scripting tools to improve workflow efficiency.
Assist in development and evaluation of machine learning or deep learning models supporting virtual compound libraries.
Collaborate with scientists and engineers to test new ideas, troubleshoot issues, and iterate on computational designs.
Document workflows, results, and methodologies to support reproducibility and knowledge sharing.