Data Science & Machine Learning Intern: Small Molecule Machine Learning

The OpportunityGlobal drug development productivity is declining exponentially, with an overall failure to develop effective treatments for many increasingly prevalent complex diseases affecting millions of patients per year. We seek to solve this by combining cutting-edge machine learning techniques with recent advances in life sciences to drastically improve how drugs are discovered and developed.
This summer we are looking for highly motivated interns looking to work at the intersection of machine learning and life sciences. As a small molecule machine learning intern, you will lead the development of cutting edge machine learning methods that solve key problems in the drug development process. Specifically you will: 1). Implement, extend, train, validate, and test the performance of cutting-edge models applied to both publicly available datasets, and large-scale internal small molecule datasets from our DNA-encoded library screening technology. 2). Collaborate with our scientists in designing the next set of automated wet-lab experiments that will confirm the results of these models. 3). Design model interpretation techniques to help with decoding novel biological/chemical phenomena within our datasets. You will also have the opportunity to present and publish your work. 
Insitro has a highly dynamic and collaborative culture in a custom-built open office in South San Francisco. You will work closely with machine learning engineers and scientists, biologists, chemists, microscopy experts, and automation engineers. You will be mentored by one of our senior researchers, who has significant experience in machine learning for small molecule drug discovery. You will also attend our machine learning team meetings and will be exposed to a diverse set of novel technologies and machine learning concepts that tackle various biological and chemical questions. 
Join us, and help make a difference to patients!

About You- Working towards a BS, MS, or Ph.D. in an engineering, computer science, mathematics, statistics, life science, chemistry, physics, or a related discipline.- Proficiency in one or more general-purpose programming languages. We primarily use Python.- Demonstrated ability to use and develop cutting edge statistical and machine learning methods inspired by real problems.- Demonstrated ability to write high-quality, production-ready code (readable, well-tested, with well-designed APIs)- Working knowledge of computational chemistry, including virtual screening (classic QSAR modeling, structure based drug-discovery), library design, etc- Experience with at least one high-end ML development environment (Tensorflow, Pytorch, Caffe, etc) - Experience with at least one of the cheminformatics toolkits (RDKit/OpenEye/Schrodinger suite, etc)- Ability to communicate effectively and collaborate with people of diverse backgrounds and job functions.- Passion for making a difference in the world.

Nice to Have- Experience with small molecules and DNA encoded library datasets- Experience with building and debugging graph convolutional neural networks- Experience with scalable machine learning, including the application to large datasets (100TB+)Experience in Linux environment, database languages (e.g., SQL, No-SQL) and version control practices and tools such as Git or Mercurial.- Familiarity with the SciPy/PyData ecosystem (numpy, pandas, scipy, dask etc.).- Familiarity with cloud computing services (AWS or GCP).

Intern Benefits- Excellent medical, dental, and vision coverage; insitro pays 100% of premiums for employees- Excellent mental health and well-being support- Access to free onsite baristas and cafe with daily lunch and breakfast- Access to free onsite fitness center- Commuter benefits- Competitive pay- Flexible work schedule (on site and remote)About insitroinsitro is a data-driven drug discovery and development company using machine learning and data at scale to transform the way that drugs are discovered and developed for patients. insitro is developing predictive machine learning models to discover underlying biologic state based on human cohort data and in-house generated cellular data at scale. These predictive models can be brought to bear on key bottlenecks in pharmaceutical R&D to advance novel targets and patient biomarkers, design therapeutics, and inform clinical strategy. insitro is advancing a wholly owned and partnered pipeline of biologic insights and molecules in neuroscience and metabolic diseases. Since formation in mid 2018, insitro has raised over $700 million from top tech, biotech, and crossover investors and from collaborations with pharmaceutical partners. For more information on insitro, please visit the company’s website at www.insitro.com.