- Fundamental analysis and understanding of computer vision, machine learning and 3D reconstruction
- Fine-tuning and evaluation of personalized machine learning regression models to improve eye tracking performance on the most challenging cases
- Design and execute experiments to explore fundamental limitations of personalized models
- Collaborate with researchers and engineers across diverse disciplines
- Communication of research agenda, progress and results
- Currently has, or is in the process of obtaining, a PhD degree in the field of Computer Science, Applied Math, Physics or a related STEM field
- High levels of creativity and quick problem solving capabilities
- Interpersonal skills: cross-group and cross-culture collaboration
- Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment
- Experience implementing machine learning algorithms with Python and Pytorch
- 2+ years of research experience or equivalent graduate research experience in 3D computer vision and Machine Learning
- Experience developing and improving ML models through fine-tuning or transfer learning, especially unsupervised or weakly supervised learning
- Demonstrated experience managing high-dimensional data through dimensionality reduction methods, including PCA and LDA, for enhanced data interpretation
- Demonstrated software engineering experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. Github)
- Intent to return to degree-program after the completion of the internship
- Proven track record of achieving results as demonstrated in accepted papers at top computer vision and machine learning related conferences such as CVPR, ICCV, ECCV, ICLR, ICML, NeurIPS, etc.
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