Microscopy imaging has been used in many scientific applications including cell biology and material sciences. Advances in microscopy allow us to acquire terabyte-sized images. However, the current limitations of desktop computers in terms of memory, disk storage and computational power, and the lack of image processing algorithms for advanced parallel and distributed computational platforms, prevent scientists from advancing in their domains. The challenges include the facts that (1) microscopy image acquisition generates terabyte-sized images that are typically stored as thousands to millions of smaller files but have to be rendered seamlessly and interactively; (2) images need to be inspected with their surroundings of spatial, temporal and spectral information, and the neighboring image information has to be viewed from multiple viewpoints; (3) automation of image processing and its validation are necessary tasks for coping with image volumes; and (4) images need to be shared and then accessed by a team of experts. We are seeking candidates to address these challenges that range from algorithm development, simulation of reference data, algorithmic accuracy evaluations, design of parallel algorithms, execution of algorithms in the computer cloud, to delivering on-demand measurements over the Web.

 

key words

Image processing; Machine learning, Computer vision; Statistical methods; Parallel and distributed computing; Software engineering; Standards;

Citizenship:  Open to U.S. citizens

Level:  Open to Postdoctoral applicants