- Design and implement robust algorithms for laser-scanning based eye-tracking systems
- Design experiments, collect data, and analyze data with and without humans-in-the-loop to de-couple and quantify eye tracking error sources
- Derive first-order paper studies to better understand the trade space in comparison to conventional camera-based glint/pupil tracking methods
- Collaborate with researchers and engineers across diverse disciplines through all stages of project development
- Regular communication of research agenda, progress and results
- Publish research results in top-tier journals and at leading international conferences
- Currently has or is in the process of obtaining a PhD in the field of Computer Science, Optics, Biomedical Engineering, Electrical Engineering, Applied Physics, or a related STEM field
- 2+ years experience with computer vision, image processing, optimization, calibration, image stitching, eye tracking, retinal imaging, or related topics
- 2+ years experience with scientific programming languages such as MATLAB or Python
- Hands-on experience working with custom research-grade imaging and sensing systems
- Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment
- Experience with one or more of the following: simultaneous localization and mapping (SLAM), automatic montaging methods, eye tracking, retinal imaging, machine learning, sensor fusion, laser scanning systems
- 2+ years experience in C/C++
- Experience with deep learning frameworks (Pytorch, Tensorflow, etc)
- Demonstrated programming experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. Github)
- Broad, end-to-end understanding of all aspects of tracking objects in 3D space (i.e. hardware, firmware, software, algorithm, analysis, evaluation)
- Experience with basic optical systems, with an emphasis on the optics of the human eye
- Past experience with cross-group and cross-culture collaboration
- Proven track record of achieving significant results as demonstrated by first-authored publications in journals or at conferences, etc.
- Intent to return to degree-program after the completion of the internship
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