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RoadEO is developing a road quality monitoring and prediction platform which advises public and private road authorities when and where the next road segment needs to be maintained. For this we are combining satellite imagery, crowdsourced smartphones and in-car sensors to create a novel and innovative data source which we then interpret with the help of machine learning algorithms.
This is your chance to be part of it! We are in the exciting phase of growing our enterprise and are looking for a key team member helping our clients to reduce maintenance efforts, improve road safety and decrease global CO2 emissions.
Roles & Responsibilities
You will lead our software development efforts from our current web and mobile prototypes to a fully functioning, reliable system. This includes the whole product development spectrum from gathering requirements to implementing our solution with our customers.
Your responsibilities will be:
Profile
We are looking for somebody who has:
In return we want to offer you this unique opportunity for professional and personal development while not only leaving a mark in society but also at the very core of our company DNA! We secured first funding through grants and our launching customers such as the Royal BAM Group and the Municipality of Leiden and have an exciting pipeline of customers from all around the world.
About us
RoadEO is a social enterprise with the goal of using space technology for social and environmental good. Originated from winning the European Satellite Navigation Competition (ESNC), we are now part of the European Space Agency (ESA) Incubation Program, the Impact!Hub social enterprise network and collaborate with Verhaert and TU Delft. RoadEO is located at the ESA Business Incubation Centre Noordwijk, The Netherlands, while changing location to either The Hague, Utrecht or Amsterdam in 2020.
RoadEO is developing a road quality monitoring and prediction platform which advises public and private road authorities when and where the next road segment needs to be maintained. For this we are combining satellite imagery, crowdsourced smartphones and in-car sensors to create a novel and innovative data source which we then interpret with the help of machine learning algorithms.
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