Vectech builds AI-powered tools that identify mosquitoes and ticks from images, helping public health organizations make faster, smarter decisions about vector control. Our computer vision models are deployed in the real world, across diverse geographic regions with local species variants and unfamiliar phenotypes. Understanding how that diversity affects model behavior is a key challenge in maintaining reliable deployed systems. This internship continues work initiated over the summer on dataset drift and model behavior in real-world deployments. You'll focus on analyzing factors indicative of dataset drift, and on understanding how our models behave when faced with largely unlabeled data — specimen images without expert identification. This is a part-time role designed to fit around an academic schedule, with meaningful research contributions expected throughout the year.
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Job Type
Part-time
Career Level
Intern
Education Level
No Education Listed