Share Your Research, Maximize Your Social Impacts
Main Menu
Searching By
Main Menu
PARTNERS
PhD Fellowship in Big data processing and management in smart community - University of Quebec
Country/Region : Canada
Website : http://www.synchromedia.ca
Description
The Synchromedia Lab (http://www.synchromedia.ca) at the Ecole de Technologie Superieure (University of Quebec) is seeking for a PhD candidate with a specialty in big data processing and management in smart community.
In a smart home and smart community, networked M2M devices generate various traffic patterns, including periodic, event-driven, generated amounts, and multimedia streaming patterns, depending on their applications, which is a valuable source to make decisions on home automation and smart community management. Big data processing and mining aims to improve not only the control of communications network, but also to monitor user and system behaviour all the time and store the data, getting several parameters through different devices to always ensure the well-being and the home control. A cloud based framework for statistical data processing is required based on the parallel processing paradigms.
This PhD project will be dedicated to big data modelling and predictive machine learning for smart services in a networked community. The candidate will investigate and develop statistical processing methods to build models for gather data on consumption, emissions, and behaviours of actors involved in the smart home and cloud. A platform for big data storage and management will be developed, as well as patterns and models characterizing real-time operational status of smart home appliances, cloud resources and users over time. He/She will then propose state-of-the-art algorithms for processing query big databases, analyzing behaviors, and optimizing operations on knowledge bases.
Required qualifications:
- Strong background data mining, machine learning and/or data storage and management
- Good knowledge in optimization techniques
- Excellent programming skills
- Good communication and writing skills
Applications shall include a CV, transcripts, and a cover letter. Selected applicants will be contacted for an interview.
In a smart home and smart community, networked M2M devices generate various traffic patterns, including periodic, event-driven, generated amounts, and multimedia streaming patterns, depending on their applications, which is a valuable source to make decisions on home automation and smart community management. Big data processing and mining aims to improve not only the control of communications network, but also to monitor user and system behaviour all the time and store the data, getting several parameters through different devices to always ensure the well-being and the home control. A cloud based framework for statistical data processing is required based on the parallel processing paradigms.
This PhD project will be dedicated to big data modelling and predictive machine learning for smart services in a networked community. The candidate will investigate and develop statistical processing methods to build models for gather data on consumption, emissions, and behaviours of actors involved in the smart home and cloud. A platform for big data storage and management will be developed, as well as patterns and models characterizing real-time operational status of smart home appliances, cloud resources and users over time. He/She will then propose state-of-the-art algorithms for processing query big databases, analyzing behaviors, and optimizing operations on knowledge bases.
Required qualifications:
- Strong background data mining, machine learning and/or data storage and management
- Good knowledge in optimization techniques
- Excellent programming skills
- Good communication and writing skills
Applications shall include a CV, transcripts, and a cover letter. Selected applicants will be contacted for an interview.
Last modified: 2017-05-13 11:25:56