AI Scientist, Algorithms

Employment Type

: Full-Time

Industry

: Miscellaneous



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 multifaceted backgrounds to help us achieve our mission. Our team includes artificial intelligence scientists, computational biologists, 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 required. The future of genetics depends on newer 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 who can design and implement forward-looking research initiatives. You are an expert in a domain such as probabilistic machine learning, Bayesian hierarchical regression, causal inference, or deep learning algorithm development. You are hard-working 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 partners. You take pride in writing robust, readable, and idiomatic code. You appreciate the novelty and difficulty of academic research, and enjoy the opportunities for impact, focus, and scale of industrial research. What you'll do: * Perform 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 multiple partners, software engineers, laboratory scientists, and 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 probabilistic machine learning * Expertise in statistics, especially Bayesian methods * Experience with deep learning concepts and practice * Prior experience with sparse regression and causal inference is a major plus * Direct experience with genetic or biological data is a plus * Ability and willingness to learn unfamiliar concepts * Keenness for documentation and detailed planning * Minimum of PhD or equivalent research experience in applied mathematics, computer science, or a quantitative biology, additionally research experience is a plus * Expert in Python 3 and numerical libraries (e.g. numpy, scipy, pytorch, tensorflow) * Experience using or developing high-performance computation on large datasets (ideally from clinical, genomic, or other 'omics' 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. #LI-Remote

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