Yale Peabody Museum Summer Internships

Development of High-Throughput Methods for Mass 3D Digitization of Natural History Collections

Advisor: Nelson Rios (YPM Head of Biodiversity Informatics and Data Science)


Length: 8 weeks in the summer


Project Description:

Collectively, the number of biological specimens in U.S. museums and herbaria exceeds 500 million. The number worldwide is estimated to be nearly 3 billion with more than 90 percent of associated data still locked away in cabinets, ledgers, labels and other physical archives. Over the past three decades, digitization initiatives have focused on bringing this “dark data” into the light of the digital world. These efforts traditionally focused on capturing and enhancing textual "label data" but recent years have seen a greater research demand for specimen imaging. Scientists increasingly rely upon high-resolution two-dimensional imagery for morphological analysis of specimens, utilizing landmarks or shape-based approaches. These approaches are well suited to relatively flat structures, but have drawbacks when applied to three-dimensional structures, thereby limiting our ability to thoroughly characterize specimens and their traits. Generating natural-color, 3D representations of specimens may provide a solution, yet little progress has been made implementing robust, production-level methodologies for 3D data capture at scale. To meet the growing need for digitization at scale, new workflows and technologies that enable high throughput data capture from natural history specimens will need to be pioneered. As part of an existing project to develop instrumentation for high-throughput, multi-view imaging (useful for 3D reconstruction), we seek an intern to assist in the development of hardware and software for structured-light imaging. Experience programming in C and/or Python required. Experience with CAD preferred.


Stipend: $3000