This position is offered through the ANU Computing Internship courses (COMP4820 / COMP8830).
Semester 2, 2026 applications open on Monday 18th May 2026 and close on Sunday 31st May 2026.
Company
Clairva.ai is a Singapore-incorporated startup building licensed video and audio data infrastructure for multimodal AI training. We source content from global media libraries and commission specialised video data collection, then produce annotated datasets that meet Tier-1 ingestion standards for foundation-model labs and dataset platforms. We prioritise rights-cleared provenance and high-quality annotation pipelines.
Project
Clairva.ai is a Singapore startup working with licensed video and audio data for multimodal AI training. The next wave of robot learning uses neuromorphic event cameras. These include Prophesee GenX320, Sony IMX636, and iniVation DAVIS346. Event cameras are asynchronous and have microsecond latency. They are used in high-speed manipulation, drones, and reactive RL. Research papers using event-stream data for reinforcement learning have grown sharply since 2023.
In this placement you will produce a written research brief with citations. Your brief will map the current state of event-camera data for robotics and RL. It should also explore how event streams relate to existing video-annotation schemas.
- You will survey current commercial event-camera sensors.
- Survey public event-camera datasets. Examples are DSEC, MVSEC, M3ED, N-CARS, EventVLAD, and V2E-simulated streams.
- Scan 15 to 20 recent papers from 2023 to 2026. These should use event-stream input for RL, imitation learning, or world-model training.
- Sketch how event streams could fit existing video-annotation schemas.
- Map the research community working in this area.
- Write a structured set of findings and open questions.
Required technical skills
Required skills are strong literature-search and synthesis abilities. Python 3.10+ for any small exploratory scripts is needed.
Comfort reading robotics and computer-vision papers is expected.
Preferred skills are prior coursework in robotics, computer vision, or reinforcement learning. Familiarity with the broad ML research field is a plus. Basic awareness of hardware specifications also helps
Required/preferred professional and other skills
Required skills are excellent technical writing for a non-academic audience. The student should produce executive-summary-quality output. Structured note-taking and citation management are needed. Clear synthesis of conflicting sources is expected. Preferred skills are prior experience writing literature reviews or technical reports.
Delivery Mode
Hybrid
Student location
Project’s Special Requirements/ Conditions
None
Type of internship
Unpaid
How to apply
Applications are invited from eligible students to apply for the Computing Internship courses COMP4820 or COMP8830. Eligibility details of COMP4820 / COMP8830 and further information about the Computing Internship can be found on the Computing Internship page.
Eligible students can apply through the Computing Internship application form which will be available via the Computing Internship page between Monday 18th May 2026 and close on Sunday 31st May 2026.
You can nominate multiple preferred Internship projects and host organisations through the one online application form.
Eligibility and room available in degree to undertake COMP4820/COMP8830 will be assessed at the time of application. If you do not meet the eligibility criteria or do not have room in your degree to fit COMP4820/COMP8830, your application will not be progressed.
Your application will require you to upload the following documents:
- an updated copy of your resume, and
- an expression of interest (limit 350 words) for each organisation you wish to apply to (organisations with multiple projects may only submit one expression of interest, so state clearly which project/s you wish to be considered for).