The staffs within School are widely published and attract highly competitive grants and industry sponsorship. In 2019, each faculty member attracted more than $US57000 worth research or industry grants in average. Moreover, the use of QR-code to trace a person’s health condition in prevention of corona-virus was first proposed and implemented by a research team of SCDE, which was fully adopted, extended and promoted nationwide later on.
We value research as a fundamental form of learning. Success requires collaboration, not just between scholars, but with community, industry and government. SCDE has three major research groups:
Computer and data Science group develops innovative solutions that create value from data, across all stages of its life cycle, to facilitate better decisions and gain deeper knowledge, researches and develops innovative and practical solutions for business, scientific and social applications in the realm of big data. This group encompasses a variety of research strengths including: Data and knowledge engineering, surveillance, complex and intelligent systems, and eHealth services.
Computer vision and AI group mainly focuses on developing fundamental theories and algorithms in the field of computer graphics, computer vision, and artificial intelligence. The research work includes a variety of topics, such as face recognition, image retrieval, semantic analysis of 2D images, 3D shapes, or 3D point cloud, deep learning, etc. Applying those algorithms to industrial manufacturing and smart cities for increasing productivity or improving management efficiency is also an important part of the research work.
Digital Pathology group is to develop technologies that make pathology workflows much faster and more efficient. The project utilizes qualified data compression methods, computer vision, machine learning and pattern recognition methods to create digital pathology scanning systems. The research covers the fields of image analysis and bio-signal analysis, with a focus on developing new tools to improve data acquisition, data reconstruction and analysis from medical images and stream data.
• Full-Time Lectures/Associate Professors/Professors in Computer and Data Sciences.
• Full-Time PhD students (4 years each, scholarship and tuition fee waiver included)
REQUIRED SKILLS: knowledge of process mining/machine learning/algorithm, programming (Java, Python/R).
DESIRED SKILLS: knowledge of deep learning and active learning algorithms.
WORKING HOURS: Full-Time PhD students.
LOCATION: Ningbo, Zhejiang University of Ningbo Campus
HOW TO APPLY: Contact Prof Chaoyi Pang (firstname.lastname@example.org) for further details.