Computational Chemistry Intern - 2026

Genesis Therapeutics is bringing together a world-class computational team to build out the industry's fastest and most accurate small molecule property predictions, by combining the power of machine learning and physics-based methods. We are seeking early career scientists skilled in developing and applying computational chemistry and physics methodologies to help drive forward our challenging drug discovery programs.

You will

• Develop and refine advanced computational chemistry and physics methodologies to help solve pressing challenges in our internal drug discovery programs

• Collaborate with our machine learning team on hybrid physics/ML methods for predicting structure, potency, and other properties relevant to drug discovery.

• Work closely with our computer-aided drug discovery scientists and medicinal chemists to develop, benchmark, and deploy improvements to our drug discovery platform as it is applied to our internal and partnered drug discovery programs.

You are

• A graduate student with a proven track record of applying or developing computational chemistry and physics methods.

• Passionate about building methods to solve real problems.

• A skilled programmer, preferably in Python, such that you can quickly implement your research ideas and analyze their performance.

What we offer

• The opportunity to work on challenging, high impact computational chemistry research that is immediately deployed to accelerate the discovery of new medicines.

• A world-class, tight-knit team of good-hearted people across software, machine learning, computational chemistry, medicinal chemistry, and biology.

• Competitive salary and equity. Medical, dental, and vision insurance, and a 401(k) program.

• One-on-one mentor to help guide your research and act as a point person for questions.

Application & Hiring Timeline

• Application Deadline: January 9, 2026

• Resume Review: Beginning January 12, 2026

• Interviews Kick-Off: January 26, 2026

• Target Start Date: May–June 2026