Notable Labs

San Francisco
26 - 50 Employees
< 10 Engineers
$10M - $25M Funding
Series A

We're building a personalized drug discovery platform to identify treatment options for relapsed and refractory cancer patients — starting with blood cancer — to address the long tail of cancer treatment. We look at a person’s actual cancer cells, test combinations of FDA approved drugs, and see which combinations kill the cancer cells and leave the healthy cells alive. We focus on combinations because cancer is often difficult to target with just one drug and starting with a single drug can lead to resistant clones or relapse. We're building a highly automated lab in Foster City running on our custom software (Python/Django, JavaScript/React, PostgreSQL), and are currently testing relapsed/refractory cancer patients as well as samples from a variety of pharma/biotech partnerships.


Why join us?
  • Use a modern tech stack to directly fight cancer, one patient at a time

  • Work in a collaborative interdisciplinary environment on multi-functional project teams of: software engineers, automation engineers, data scientists, machine learning experts, bioengineers, computational biologists, process engineers, immunologists, clinical and R&D scientists, etc.

  • Learn about the state of the art in cancer treatment with a team dedicated to both personal and scientific growth and development

  • Well funded with over $17M (series A) from Builders Venture Capital, Founders Fund, First Round Capital, Y Combinator, several prominent angels and seed-stage funds, and Accelerate Brain Cancer Cure, a venture philanthropy firm founded by Steve Case


Engineering at Notable Labs
Engineering team and processes

Our engineering team consists of three functional area: software engineering, lab automation engineering, and bioinformatics. We work in two-week cycles that start with a planning meeting to discuss features/timelines and end with a demo/retrospective. Engineers work closely with both the PM and the science and business development teams to spec features. We use GitHub and pull requests for code reviews. Everyone is responsible for testing their own code and we use CircleCI for CI/CD which enables all engineers to push to production after review.

Technical Challenges

Oncology and immunology data is complex and the engineers at Notable Labs build data-rich web applications for scientists and laboratory users to visualize scientific data, talk to robots, drive laboratory workflows, organize medical knowledge, and facilitate cancer treatment discovery. To grow beyond the limits of manual data analysis we are actively applying machine learning techniques to the interpretation and review of this data. In addition to helping individual patients, we're creating novel datasets of drug and immune responses in primary samples that can be mined to discover new therapeutics and build decision support systems for clinicians.

Projects you might work on
  • Build a web application that allows scientists to create templated workflows that inferface with our robotic lab.

  • Build an automated PDF report of a patient's drug sensitivity compared to all the historical results in a disease indication for use in a clinical trial.

  • Create a machine learning pipeline to automate the interpretation of flow cytometry data.

Tech stack
Ruby on Rails
PostgreSQL
Python
Javascript
React
Django

Working at Notable Labs

Have compassion for patients above all else. Believe that all cancers can be treated. Celebrate life. Support and respect everyone. Work with passion. Act as a collaborative hub for our community. Make empirically data driven decisions. Be relentlessly resourceful. Foster a learning organization.

Free Food
Generous Vacation
Workshops/Conferences
Maternal/Paternal Leave
Flexible Hours
Team Activities
Work from Home

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