Subventions et des contributions :

Titre :
Learning to match applicants to job profiles
Numéro de l’entente :
EGP
Valeur d'entente :
25 000,00 $
Date d'entente :
7 mars 2018 -
Organisation :
Conseil de recherches en sciences naturelles et en génie du Canada
Location :
Ontario, Autre, CA
Numéro de référence :
GC-2017-Q4-00263
Type d'entente :
subvention
Type de rapport :
Subventions et des contributions
Informations supplémentaires :

Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier (2017-2018 à 2018-2019).

Nom légal du bénéficiaire :
Bruce, Neil (Ryerson University)
Programme :
Subventions d'engagement partenarial pour les universités
But du programme :

The proposed research activities will help to improve capabilities in matching prospective job applicants tox000D
jobs posted by hiring managers seeking suitable candidates. This is a research endeavor grounded in machinex000D
learning, data science and neural networks towards extracting maximum value from data, and providing bestx000D
possible matches, and outcomes in hiring.x000D
The proposed research will help with decision making based on large and heterogeneous data, also providingx000D
new capabilities, and scalability in new directions with potential for exponential growth. Data consideredx000D
ranges from text based candidate descriptions to more targeted measures that inform on quality of fit in fillingx000D
jobs.x000D
Modern advances in AI and deep learning will be applied, alongside careful principles of system design tox000D
provide optimal matches, and successful outcomes post-hire.