Summer Intern, Computational Discovery Chemistry

Arrowhead Pharmaceuticals•Madison, WI

8h•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 Position The Computational Discovery Chemistry Intern will join Arrowhead Pharmaceuticals’ Discovery Research organization and play an active role in contributing to the expansion of data infrastructure and computational tools within the Computational Chemistry Core. This this role will focus on database development, data analysis, and coding of new tools that support in-silico drug design and AI/ML-driven discovery efforts. The intern will work under the guidance of senior scientists and computational leaders, gaining exposure to applied data science, bioinformatics, and machine learning within a pharmaceutical research environment. This is an 11-week Summer Internship Program paying $21.00 per hour and requires full-time, onsite work five days per week at the designated location.

Requirements

Currently enrolled in a bachelor’s degree program at an accredited university or college and majoring in computer science or a related field.
Basic command-line experience (Bash/Shell) in Unix and/or Linux environments.
Experience coding in Python (preferred), or demonstrated proficiency in Julia, JavaScript/TypeScript, or R.
Experience with relational databases and query languages such as SQL.
Excellent verbal and written communication skills, including comfort presenting in group settings.
Strong problem-solving and organizational skills.
Proficiency in Microsoft Office applications.
Ability to lift up to 40 lbs.
Willingness and ability to spend 25% of the workday walking the facility and 75% at a desk.

Nice To Haves

Exposure to applied bioinformatics, including HTC/HPC environments and/or HT-seq analysis.
Interest in AI/ML applications within drug discovery and computational chemistry.
Strong curiosity, initiative, and eagerness to build scalable tools in a scientific research setting.

Responsibilities

Expand and maintain databases supporting computational chemistry and discovery research initiatives.
Program new tools for automated data extraction to support both new and existing databases.
Develop tools for quality control (QC) analysis of biological efficacy data and apply them to collected datasets.
Create tools for streamlined processing of in-silico–generated data.
Contribute to ongoing discovery efforts, including: Development of generative AI / machine learning models for physicochemical and structural prediction of drug molecules. Development of models integrating biological, bioinformatic, and in-silico calculated data.
Assist with data analysis, visualization, and interpretation to support applied drug discovery efforts.
Collaborate with computational chemists, data scientists, and discovery stakeholders.
Present project updates in weekly group meetings.
Prepare final deliverables, including a scientific poster and a ~20-minute presentation summarizing project objectives, results, and learning.