Statistics Internship Summer 2024
We are advancing AI to power the future of medicine.
At Unlearn, our purpose is to advance artificial intelligence (AI) to eliminate trial and error in medicine. We are innovating advanced machine learning methods to leverage generative AI in forecasting patient outcomes, starting with the domain of clinical trials. We produce AI-generated digital twins of individual trial participants, enabling smaller and more efficient clinical trials to bring effective medicines to patients sooner.
Our innovative work in AI today will reinvent how AI is applied in medicine tomorrow — and we have a top secret plan for how to get there. We won’t be able to achieve this mission just by applying technologies created by others; the future must be invented.
Unlearn is a technology company, not a biotech company. We use computers, not pipettes. We make and use software, we don’t discover or make drugs. We believe that AI will define the future of medicine, and we aren’t deterred by naysayers or skeptics.
We come from a variety of backgrounds ranging from machine learning to marketing—but regardless of where we come from, Unlearners share some common traits:
Unlearners are ambitious; we aren’t intimidated by big, challenging goals.
Unlearners are disciplined experimenters; we break down our big goals into smaller chunks and meet as often as necessary to track our velocity and iterate quickly.
Unlearners are gritty; we never give up, setbacks just make us try harder.
Unlearners are receptive to new ideas; in fact, we hate being stuck with the status quo
Unlearners are storytellers; sharing information with each other and with the world is super important, too important to be boring. And, last but not least,
Unlearners are team-oriented; we put the mission first, the company second, the team third, and individuals last.
Headquartered in San Francisco, with an additional office in Boston, Unlearn was founded in 2017 by a team of world-class machine learning scientists. We have raised venture capital from top tier investors such as Altimeter, Insight Partners, Radical Ventures, 8VC, DCVC, and DCVC Bio, and recently completed our $50 million Series C in January 2024.
If our purpose and culture resonate with you, we invite you to apply.
The Role
This internship will involve working with Research Statisticians to develop a standardized base for statistical computing for clinical trials that bridges programming languages. This base will need to be readily scalable in terms of its ability to accommodate new statistical methodologies and handle large computations, for different types of clinical trials. The product will become a core component of statistical workstreams and increase team efficiencies.
Requirements
Applicants must be pursuing a Master’s or PhD in Statistics, Computer Science, Applied Mathematics, or related quantitative fields.
Knowledge of R and Python.
Experience with Git and GitHub.
Experience working and communicating with cross-functional and/or interdisciplinary teams.
Ability to work in our San Francisco office at least 2-3 days per week.
Preferred
Experience with Slurm/cluster computing.
Experience with statistical simulation and computation.
Responsibilities
Work with Research Statisticians to establish standards for computational processes.
Write code templates and documentation in Python and R.
Work with platform engineers to integrate code and work streams.
Identify and adopt new computational tools when necessary.
Communicate codes to different audiences at Unlearn.
Benefits & Perks
Generous equity participation
100% company-covered medical, dental, & vision insurance plans
401k plan with generous matching
Flexible PTO plus company holidays
Annual company-wide break December 24 through January 1
Professional development budget to attend conferences or other events
Commuter benefits plan
Paid Parental Leave
Unlearn is an equal opportunity employer.
At Unlearn, we are committed to building a diverse and inclusive workplace, because inclusion and diversity are essential to achieving our mission. If you’re excited about this role, and your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply nevertheless.