Deep Learning Internship Opportunities at JPL

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Deep Learning Internship Opportunities at JPL

UC San Diego

icon La Jolla, CA, US, 92037

iconIntern

icon26 September 2024

Job Expired
1012225
JPL

Deep Learning Internship Opportunities at JPL

The Jet Propulsion Laboratory (JPL) is NASA’s lead center for robotic exploration of the solar system. We aim to do things never done before and to go places few can go.

We do research differently here at JPL. We work on fundamental research problems leading to unique artificial intelligence applications in spacecraft autonomy, scientific data analysis, and mission operations automation and onboard analysis for real-time decisions. 

Research Scientists aren't cloistered in the lab, but instead work closely with roboticists and scientists to discover, invent and build automation systems for ground and flight operations, space missions, marine vehicles, aerial vehicles, and swarms of vehicles.

To achieve this, we’re working on projects that utilize the latest techniques in Machine Learning (including Deep Learning approaches). We’ve already been joined by some of the best minds, and we’re looking for talented Research Scientist Interns and Software Engineer Interns that have applied experience in the fields of optimization for deep learning, deep reinforcement learning for robotics, natural language understanding, imitation learning, meta-learning, nonconvex optimization, and machine intelligence to work with our team.

From creating experiments and prototyping implementations, to designing new architectures, Research Scientist and Software Engineer Interns work on challenges in machine perception, data mining, deep Q-learning, POMDP, and semi-supervised learning. In this role, you'll stay connected to your research roots by actively contributing to the wider research community, partnering with universities and publishing papers.

JPL, located in Pasadena, California, has a casual, campus-like environment situated on 177 acres in the foothills of the San Gabriel Mountains and offers a work environment unlike any other: we inspire passion, foster innovation, build collaboration, and reward excellence. We are proud to be part of NASA and Caltech, as we explore the universe and make history through new discoveries.

Responsibilities:

•    Participate in cutting-edge research in machine intelligence and deep learning applications including: optimization for deep learning, deep reinforcement learning for robotics, natural language understanding, imitation learning, meta-learning, global optimization, and machine intelligence.

•    Develop solutions for real world, large-scale problems.

Minimum qualifications:

•    Currently pursuing Ph.D. in computer science or a related technical field.

•    US citizen or permanent resident (for graduate students)

•    Experience (classroom, research, or work related) in Machine Learning, Deep Learning, Knowledge Base, Natural Language Understanding, Neural Networks, Computer Vision, Convex Optimization, Non-convex Optimization, Bayesian Optimization, Data Science, SLAM, Control Theory, Optimal Estimation, Data Mining and/or Machine Intelligence.

•    Experience with one or more general purpose programming languages, including C/C++, Java, JavaScript, Lisp, MATLAB, Python.

•    Contribution to research communities and/or efforts, including publishing papers (being listed as the author) at conferences such as NIPS, ICML, ACL, CVPR, CDC, ACC, etc.

Preferred qualifications:

•    Relevant work experience, including full-time industry experience or as a researcher in robotics and deep learning labs.

•    Demonstrated publication record, with several publications at conferences (e.g., JOGO, NIPS, ICML, ACL, CVPR, etc.).

•    Experience and background in few-shot learning and Generative Adversarial networks.

•    Ability to design and execute on a research agenda.

•    Significant experience in automation and analysis systems for timeseries data or robotic autonomous systems.

Please submit your resume and contact Dr. Alimo regarding this position. Email: shahrouz.r.alimo@jpl.nasa.gov

The internships can be extended up to one year.

Job Contact
sralimo@jpl.nasa.gov