2019 PhD Data Scientist Internship - NLP / Conversational AI
Data Science, University
At Uber, we ignite opportunity by setting the world in motion. We take on big problems to help drivers, riders, delivery partners, and eaters get moving in more than 600 cities around the world.
We welcome people from all backgrounds who seek the opportunity to help build a future where everyone and everything can move independently. If you have the curiosity, passion, and collaborative spirit, work with us, and let’s move the world forward, together.
About the Role
This internship role involves bringing cutting edge Natural Language Processing and Conversational AI technologies to Uber, as well as developing state of the art algorithms in these fields.
What You’ll Do
Collaborate with different scientists at Uber to define the project you will be working on
Conduct literature review on the project
Potentially invent new approaches to solving the problem in hand
Implement the solutions and provide analysis of the discovered results
What You’ll Need
Ph.D. student (anticipated graduation in 2020) in computer science or related disciplines
Strong background in Machine Learning and Deep Learning
Strong background in Natural Language Processing, Conversational AI, or Dialog Systems
Strong command of modern Deep Learning frameworks such as Tensorflow or PyTorch
Strong programming skills in Python
Bonus Points For
Strong publications in the field
Related MSc or PhD thesis topics
About the Team
The NLP and Conversational AI is a cross-organizational team here at Uber that brings many scientists and engineers together to develop modern NLP solutions and AI-based dialog systems for Uber.
At Uber we don’t just accept difference—we celebrate it, we support it, and we thrive on it for the benefit of our employees, our products and our community. Uber is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.