Summary
The digital age has permeated our daily lives. The data we consume and create results in analytic processes informing how we work, eat, play, live. Companies need to understand, analyse and develop their Human Capital to remain competitive and future proofed.
Present technology is not serving the market effectively. CVs have long outstayed their use for employers and overburden HR systems. EU citizens need to be able to assess their skills versus a changing job market to keep pace; putting them in the best position to successfully be hired.
Our innovative approach to solving the bottleneck between jobseekers and job vacancies sets us apart. Our disruptive platform, AIRE, uses AI & Machine Learning to accurately and without bias, match candidates to roles, identify skills gaps for candidates and enable employees to keep their skills relevant in an ever-evolving job market.
Our vision will create a scalable solution to empower EU citizens to maximise their career potential. In line with our growth strategy, Allsorter is looking to employ an innovation associate to help us achieve the above goal. The post will be influenced from the domains of textual mining, machine learning and crowdsourcing. This field is novel precisely because it attempts to combine a longstanding promise of AI to improve the quality of hiring, which ability is focused around the use of data to standardize the matching between candidates’ experience, knowledge skills and the job requirements. This improvement in the job matching mechanism will utilize innovative computational methodologies for processing, improving, and disseminating employability patterns.
Present technology is not serving the market effectively. CVs have long outstayed their use for employers and overburden HR systems. EU citizens need to be able to assess their skills versus a changing job market to keep pace; putting them in the best position to successfully be hired.
Our innovative approach to solving the bottleneck between jobseekers and job vacancies sets us apart. Our disruptive platform, AIRE, uses AI & Machine Learning to accurately and without bias, match candidates to roles, identify skills gaps for candidates and enable employees to keep their skills relevant in an ever-evolving job market.
Our vision will create a scalable solution to empower EU citizens to maximise their career potential. In line with our growth strategy, Allsorter is looking to employ an innovation associate to help us achieve the above goal. The post will be influenced from the domains of textual mining, machine learning and crowdsourcing. This field is novel precisely because it attempts to combine a longstanding promise of AI to improve the quality of hiring, which ability is focused around the use of data to standardize the matching between candidates’ experience, knowledge skills and the job requirements. This improvement in the job matching mechanism will utilize innovative computational methodologies for processing, improving, and disseminating employability patterns.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/861888 |
| Start date: | 01-10-2019 |
| End date: | 28-02-2021 |
| Total budget - Public funding: | 98 750,00 Euro - 98 750,00 Euro |
Cordis data
Original description
The digital age has permeated our daily lives. The data we consume and create results in analytic processes informing how we work, eat, play, live. Companies need to understand, analyse and develop their Human Capital to remain competitive and future proofed.Present technology is not serving the market effectively. CVs have long outstayed their use for employers and overburden HR systems. EU citizens need to be able to assess their skills versus a changing job market to keep pace; putting them in the best position to successfully be hired.
Our innovative approach to solving the bottleneck between jobseekers and job vacancies sets us apart. Our disruptive platform, AIRE, uses AI & Machine Learning to accurately and without bias, match candidates to roles, identify skills gaps for candidates and enable employees to keep their skills relevant in an ever-evolving job market.
Our vision will create a scalable solution to empower EU citizens to maximise their career potential. In line with our growth strategy, Allsorter is looking to employ an innovation associate to help us achieve the above goal. The post will be influenced from the domains of textual mining, machine learning and crowdsourcing. This field is novel precisely because it attempts to combine a longstanding promise of AI to improve the quality of hiring, which ability is focused around the use of data to standardize the matching between candidates’ experience, knowledge skills and the job requirements. This improvement in the job matching mechanism will utilize innovative computational methodologies for processing, improving, and disseminating employability patterns.
Status
CLOSEDCall topic
INNOSUP-02-2019-2020Update Date
27-10-2022
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