Applied BioMath is looking for a highly determined frontend engineer to join our software engineering group. The mission of our group is to deliver cloud based modeling and simulation solutions to scientists, in support of better, cheaper, and faster drug development.

As a frontend engineer, you will enable our users with beautiful, durable, and performant software. You will architect and implement frontends of multiple web products that leverage APIs of our distributed computing infrastructure. You will contribute to shaping the user experience, design, and workflows of the products you work on. You will ensure quality through contributing to our automated test suites. 

This opportunity requires excellent communication with both other engineers and scientists. In it, you will work closely with our team of biologists, mathematicians, and engineers to deliver new products and features. At its core, this position is about delivering scientific web interfaces that drive research productivity for drug development.


  • Own and implement frontends on multiple products in Angular 9+.
  • Contribute automated unit, and end-to-end tests as part of our CI/CD strategy.
  • Contribute to the design of UX/UI for the products you work on.
  • Work with stakeholders to identify and prioritize new features.


  • Comfort with collaboration in diverse environments of biologists, mathematicians, scientific programers, software developers, and other technical disciplines.
  • 5+ years of experience in modern frontend development for desktop environments with frameworks like Angular (preferred), React, Vue, or similar.
  • 2+ years of experience contributing E2E tests (Test Cafe a plus).
  • Strong sense of design for technical UIs leveraging Material Design or similar.
  • Experience leveraging REST APIs (GraphQL a plus).


  • Experience in a life sciences environment.
  • Experience with data visualization or charting (Plotly, D3, etc.).

Applied BioMath ( is revolutionizing drug invention by helping partners accelerate best in class therapeutics into the clinic. We do this by integrating disease biology, therapeutic mechanism of action, rigorous mathematics, high performance computing mathematical modeling approaches. Our analyses have assisted both large and small pharma and biotechs to: prioritize portfolios, identify knowledge gaps, prioritize and design experiments, predict optimal drug properties, support clinical trials, enable indication/patient selection, and help understand deep biology or generate testable hypotheses. Our results have reduced costs and accelerated timelines. Our approaches have been proven across multiple therapeutic areas including oncology, immunology, immuno-oncology, cardiovascular, CNS, for a multitude of indications. We work closely with drug program teams, scientists, program managers, protein engineers, and chemists, as well as senior managers, to improve the outcome of drug programs in research, development, and clinical trials. We are frequently thought of as a member of the project team.  If interested, please contact