Overview

What we do – the gist

At Recursion, we have the benefit of being able to “ask the cells for more data” in frequent, high-throughput, rich biological experiments to an extent that sets us apart from most others doing biology and disease research.

We grow human cells, make them into models of thousands of rare diseases by breaking the genes corresponding to each disease, take pictures of them using automated microscopes, computationally extract 1000 structural features like shapes and textures from every cell, and quantify the structural differences that separate diseased from healthy cells. We then apply thousands of drugs to the cells corresponding to each disease, take pictures, and identify drugs that make the cells look healthy again. These drugs get investigated by our biologists, tested in animals, and eventually become new treatments for any of the thousands of untreated genetic diseases.

What you’ll do

You’ll take a co-leading role in developing methods and building our data science platform to turn high-resolution microscope photos of cells into actionable information for our biologists. This platform is the core of our mission — transforming drug discovery into a data science problem. We’re tackling challenging problems, often with no obvious solutions, and in some cases with no right answers. But we’re a group of sharp and highly-motivated scientists and engineers with diverse backgrounds and we’re making rapid progress.

The high-level job description has only one item: do whatever is necessary to help us progress in identifying cures for diseases. We hire the best, and trust that they are usually in the best position to decide what to try next.

Typical work includes:
Perform exploratory analysis and build creative visualizations of new types of data asking new questions.
Work with weekly experimental datasets on the order of 10 million rows (one per imaged human cell) by 1000 features.
Develop models and methods for analysis, learning and classification, using existing tools and building your own when appropriate.
Share methods with and borrow from the rest of the computational team, build a shared codebase, and collaborate on certain analyses.
Develop mature analyses into web-based tools usable by our biologists.
Add a data perspective to experimental planning and design discussions.
Suggest and design biological experiments in collaboration with our biologists to answer data-driven questions.
Present your work and pick up techniques at data and biology conferences, as desired.

What you need
Required: PhD or 3+ years experience and native-level fluency in: statistics, machine learning, coding, and answering questions in high-dimensional numerical datasets. Preferably using the Python data stack (pandas, sklearn, etc). Thorough grasp of fundamentals of machine learning such as cross-validation and learning curves. Ability to, for instance, code up custom regularization or custom visualization for a given machine learning model.
Helpful: A track record of outstanding past projects, publications, or presentations.
Very helpful: Code you can share.
Biology background is _not_ necessary. Intellectual curiosity and motivation to learn is a must, though!

About Recursion Pharma

We combine innovative biological science with machine learning and deep learning to discover new therapeutic opportunities for rare genetic diseases - or any disease that we can model in cells. Founded in 2013, we are making strides towards our ambitious goal of curing 100 diseases in just 10 years.