ML Research Intern
Genesis Therapeutics
Software Engineering, Data Science
Burlingame, CA, USA
Posted on Wednesday, September 29, 2021
Genesis is building a world-class ML team in an industry that has underutilized computational methods for too long. We are creating the best molecular generation and property prediction platform in the world, filling in a critical piece in the drug discovery process. We need you to drive the cutting-edge research that will enable us to find cures for a wider range of diseases, faster than ever before.
You will
- Drive speed and accuracy improvements in our ML platform, coming up with architecture modifications for 2D and 3D graph neural networks, and rapidly implementing and testing them in pytorch
- Keep up with deep learning research, especially pertaining to graph neural nets and graph generative models, and quickly prototype ideas gleaned from the literature
- Dive deep into molecular datasets, creating statistically rigorous train, valid, and test sets to optimally train our models for real-world prediction and generation tasks
- Develop creative featurizations of 2D and 3D molecular structures that are inspired by laws of physics and chemistry, enabling our networks to take better advantage of available data
- Work closely with software engineers and medicinal chemists to make our ML platform maximally adaptive to different use cases
You are
- A strong software engineer who will write code quickly and uphold our code quality standards
- A deep thinker who reasons from first principles over pattern matching
- Interested in learning about biochemistry and the drug development process
What we offer
- The opportunity to work on challenging, high impact ML research that is immediately deployed to accelerate the discovery of new medicines
- One-on-one mentorship to help guide your research and act as a point person for questions
- Strong technical coworkers in AI, software, and chemistry, who all have a powerful mix of intellectual curiosity and humility. The team reads and discusses 1-2 ML or chemistry papers every week to stay on top of the field and inspire new ideas