Disney Research Zurich is seeking qualified and motivated applicants for a postdoctoral research position in machine learning and artificial intelligence. The ideal candidate will have strong preparation in the theoretical fundamentals of machine learning as well as practical, hands-on experience implementing methods within various platforms (primarily Python-based, although experience with MATLAB, R, Mathematica, or other scientific-programming platforms would be useful). The main areas of research within our group include latent-variable models, representation learning, probabilistic and generative models, and various theoretical and practical aspects of deep-learning architectures. A firm grounding in or familiarity with computer-vision methodology would also be helpful. Those with backgrounds in psychology or cognitive science who are comfortable with the methods and platforms mentioned above and align with our group’s research interests are strongly encouraged to apply.
We invite applicants for a Post-Doctoral Associate position, with terms up to 2 years.
The ideal candidate will have recently completed a Ph.D. thesis in a related field and demonstrated peer-reviewed publications. Areas of interest include (though not limited to):
- Artificial Intelligence
- Natural Language Processing Dialog systems
- Computer vision
- Image Recognition
- Machine Learning
- Social robotics
- Dialog systems
- Knowledge representation and reasoning
- Autonomous Agents
Excellent written and spoken English communication skills are essential.
The Disney Research Labs provide a research foundation for the many business units within The Walt Disney Company. These include Walt Disney Imagineering, Parks & Resorts, Walt Disney Feature Animation, Walt Disney Studios Motion Pictures, Disney Interactive Media Group, ESPN, and Pixar Animation Studios. Disney Research has sibling labs located in Los Angeles and Zurich.
Full participation in the global research community is required through publication of results, collaboration with universities, and participation in professional service activities. Candidates should have a strong record of achievement in applied research, excellent academic credentials, and an earned Ph.D. in their area of specialization.