Applications for this job are now closed
Closing soon
The deep learning revolution has enabled novel applications in many domains such as vision, speech, natural language processing, and gaming. In the Machine Intelligence group we push the boundary of deep learning technology by inventing novel models and algorithms for challenging applications.
The Role
Towards these goals we are looking for highly motivated interns on the following topics:
- Neural networks applicable to graph-structured data such as molecules or programs.
- Compilers and acceleration methods for deep learning training and inference.
- Probabilistic deep learning: Bayesian deep learning, uncertainty quantification, and sequential decision making under uncertainty.
Responsibilities
- Design, implementation, and experimental validation of deep learning models and algorithms.
- Collaboration with other researchers and engineers as part of a project team.
- Clearly communicating research ideas and results in writing, such as research papers, presentations, or research notes for internal and external audiences.
Requirements
- Deep understanding and demonstrated research track record of deep learning techniques, for example through active research in a related PhD program or equivalent research experience.
- Papers in academic conferences (NeurIPS, ICML, ICLR, AAAI or domain-specific conferences).
- Experience in building machine learning systems with PyTorch.
- Demonstrated ability to write good quality code, strong programming abilities in Python, comfortable with using Git and GitHub processes such as code reviews, and software testing principles
Benefits
- Industry leading healthcare
- Giving programs
- Opportunities to network and connect
- Discounts on products and services
