AI Scientist, Research Team

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Invitae is dedicated to bringing comprehensive genetic information into mainstream medicine to improve healthcare for billions of people. Our team is driven to make a difference for the patients we serve. We are leading the transformation of the genetics industry, by making clinical-grade genetic information affordable and accessible to guide health decisions across all stages of life. 

The Invitae Research Team needs scientists with diverse backgrounds to help us achieve our mission. Our team includes computational biologists, computer scientists, and engineers working together on state of the art methods to pursue our mission. We conduct academic as well as applied research, publishing, patenting, and working with production teams as appropriate. The future of genetics depends on new methods for modeling and understanding genetic determinants of health in their personal context, and we want to bring that future to billions of people.

About you: 

You are an AI scientist with deep domain knowledge in genetics or molecular biology. You have expertise in a domain such as statistical genetics, functional genomics, or systems biology. You are enthusiastic and motivated. You break down unfamiliar problems into first principles that can be expressed with mathematics and compared to data. You can communicate technical concepts within an interdisciplinary team and outward to nontechnical stakeholders. You take pride in writing robust, readable, and idiomatic code. You appreciate the novelty and rigor of academic research, and enjoy the opportunities for impact, focus, and scale of industrial research. 

What you’ll do:

  • Perform computational biology research projects to identify, vet, and communicate strategic opportunities for the company. These projects will span simulations of innovative diagnostic approaches, development of novel algorithms for genomic medicine, and machine learning on massive internal human genetic datasets.
  • Work with internal stakeholders, software engineers, laboratory scientists, and external collaborators to integrate and scale solutions. 
  • Demonstrate insights and value internally through presentations and documentation and externally through publications, conference presentations, and blog posts.

What you bring:

  • Expertise in a domain of computational or quantitative biology
  • Familiarity with contemporary approaches to machine learning and statistical inference
  • Ability and willingness to learn unfamiliar concepts
  • Keenness for documentation and thorough planning
  • Direct experience with coalescent theory, statistical genetics, or biological sequence analysis is a major plus 
  • Minimum of PhD or equivalent research experience in applied mathematics, computer science, or a quantitative biology, additional research experience is a plus
  • Expert in Python 3 and numerical libraries (e.g. numpy, scipy, pytorch, tensorflow)
  • Strength in statistics, especially Bayesian methods
  • Experience with machine learning and deep learning concepts and practice
  • Experience using or developing high-performance computation on large datasets (ideally from human genomic, transcriptomic, or proteomic experiments)

By joining Invitae, you’ll work alongside some of the world’s experts in genetics and healthcare at the forefront of genetic medicine. We’ve created a culture that empowers our teams and our teammates to have the biggest impact and to explore their interests and capabilities. We prize freedom with accountability and offer significant flexibility, along with excellent benefits and competitive compensation in a fast-growing organization. 

Join us.

At Invitae, we value diversity and provide equal employment opportunities (EEO) to all employees and applicants without regard to race, color, religion, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance.


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Location

Conveniently located minutes from downtown Boulder via Pearl Street or the Goose Creek Path. Easily commutable from all directions.

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