Postdoctoral Researcher — EPFL
Role overview
Despite recent technological advances both in the data management and in computer architecture domains, our ability to analyze data still falls behind the unstoppable data collection rates. Data-intensive applications are increasingly more demanding in sophisticated algorithms to store, manage, and interpret data. To meet the challenges, database software needs to communicate efficiently both with the application layer and with the underlying hardware platforms, and deliver seamless computational and data management support. Research in the DIAS lab addresses both aspects of the challenge: we adapt data management technology to computer architecture trends by designing data manipulation techniques that exploit optimally the underlying hardware and I/O devices, and we enable new discoveries in scientific domains through automating physical database design and revolutionizing exploration algorithms in very large data repositories. The DIAS lab pioneers just-in-time query engines which support analytics on raw data, data cleaning and query optimization for heterogeneous distributed data, and hardware/software codesigned engines for demanding applications.
• Work closely with all members of the lab carrying out excellent research
• Supervise students and collaborate with other postdocs
Description
Despite recent technological advances both in the data management and in computer architecture domains, our ability to analyze data still falls behind the unstoppable data collection rates. Data-intensive applications are increasingly more demanding in sophisticated algorithms to store, manage, and interpret data. To meet the challenges, database software needs to communicate efficiently both with the application layer and with the underlying hardware platforms, and deliver seamless computational and data management support. Research in the DIAS lab addresses both aspects of the challenge: we adapt data management technology to computer architecture trends by designing data manipulation techniques that exploit optimally the underlying hardware and I/O devices, and we enable new discoveries in scientific domains through automating physical database design and revolutionizing exploration algorithms in very large data repositories. The DIAS lab pioneers just-in-time query engines which support analytics on raw data, data cleaning and query optimization for heterogeneous distributed data, and hardware/software codesigned engines for demanding applications.
• Work closely with all members of the lab carrying out excellent research
• Supervise students and collaborate with other postdocs
