Verily, an Alphabet company, lives at the intersection of technology, data science and healthcare. Our mission is to make the world’s health data useful so that people enjoy longer and healthier lives.
Our team combines expertise in healthcare, data science and technology to improve the health and well-being of our communities. We are developing the infrastructure and solutions to harness the profusion of health information for good. Our data-driven solutions span three primary areas: research, care and innovation. Programs include Project Baseline - our research initiative to increase participation and evidence generation in clinical research; Onduo - our personalized virtual care platform, which includes connected tools, lifestyle coaching and clinical support; and Debug - our effort to reduce the threat of mosquito-borne diseases by combining machine learning with sterile insect technique. We’re also actively working to combat the spread of COVID-19 through new programs like Healthy at Work.
Verily’s internship is a paid 13 week program for students in their graduating year of college, who are interested in working at the intersection of technology, data science and healthcare. This program is designed to expose students who have been historically underrepresented in this field to career opportunities and a pathway towards full-time employment within Verily. Students from all schools, and students who identify with a demographic that is minoritized within the technology, data science, and healthcare industries are encouraged to apply. This includes but is not limited to: Black/African-American, Latinx/Hispanic, Native American, students with disabilities, veterans, and non-binary people.
Our Data Science group specializes in analyzing and building models to help make sense of large datasets resulting from bio-sensors, digital pathology, clinical informatics, molecular assays, and patient surveys. We combine domain knowledge and programming expertise with statistical and machine learning knowledge to build scalable models and solutions that help power Verily’s various product areas. We are looking for interns with skill and interest in any of computational biology, digital pathology, clinical informatics, and bio-sensor processing.
This year our intern projects will support exciting emerging, early stage innovations in biology and pathology; novel devices deployed in clinical studies; and analysis of health system records in disease management applications. The internship project will include development and deployment of predictive models on various datasets in the aforementioned areas, as well as building specialized software infrastructure to enable the data science work.
Projects may include: application of Natural Language Processing methods to various EHR data sets for chronic disease management or clinical workflow management; developing methods for analyzing and interpreting data from the Immune Profiler platform; applications of computer vision to pathological images generated by hyperspectral microscopes; development of algorithms that extract physiological state and disease status from high-frequency bio-sensor data streams.
**Join us for a unique 13 week internship that will take place May 17th to August 13th 2021 OR June 14th to September 10th 2021
- Work with large, complex data sets to solve difficult, non-routine analytical problems.
- Apply advanced statistical and machine learning methods that relate longitudinal measurements to clinical endpoints in a real-world population.
- Develop performant and reusable models and libraries from original architecture and design through production deployment and performance analysis.
- Review literature related to the project area and integrate relevant domain knowledge.
- Communicate highly technical results and methods clearly, as well as interact cross-functionally with a wide variety of people and teams.
- Currently enrolled as a full-time student in a PhD or Master's program in a quantitative discipline (e.g., biomedical engineering, computer science, statistics, computational biology, applied mathematics, or similar) with an anticipated graduation date on or before the end of 2022. Undergraduates with demonstrated relevant experience may also be considered.
- Authorization to work in the United States.
- Experience with exploratory and statistical data analysis (such as linear models, multivariate analysis, predictive modeling, and stochastic models).
- Experience with machine learning (supervised and unsupervised methods).
- Experience with Python (most roles) and/or R (computational biology).
- Solid applied data science skills, e.g. experience with libraries such as NumPy, SciPy, Pandas, Scikit-Learn, Matplotlib etc. for Python users and dplyr, ggplot2 for R users.
- 1+ years of relevant work experience (i.e., as a biomedical engineer, data scientist, computational biologist), including deep expertise and experience with statistical data analysis.
- Experience with Deep Learning frameworks (TensorFlow, PyTorch etc.).
- Experience deploying and monitoring models in production platforms.
- Familiarity with software engineering practices and experience developing production software.
- Demonstrated willingness to both teach others and learn new techniques.