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Internship | Computer vision internship
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About this position
Detecting elements on building facades and roofs and enrich a database of the building stock in order to accelerate the energy transition in construction. Do you envision it? Become a machine learning engineer at TNO in Delft. All houses energy neutral by . For the construction sector, this is one of the biggest challenges ever. The largest hurdle is the renovation of existing houses, of which there are 8 million in the Netherlands. The current approach of renovating them one by one is not an option. That is why TNO has developed the revolutionary ‘contingentenaanpak’. It consists of helping the sector find clusters of houses with similar characteristics to which renovation concepts can be applied in similar fashion, enabling industrialization and speeding up renovation processes. How do we cluster houses? With a set of features describing the housing stock on one hand, and some track record data used as label on the other hand (we make what we call clusters of houses but we mainly apply classifications models, not clustering techniques). This methodology is the core of the so called Clustertool software we developed therefore. As a data scientist, you will work on the development of crucial image based features from street view and aerial images which are crucial to improve the performance of the Clustertool. This is how you contribute to the world of tomorrow.
What will be your role?
We have already successfully deployed the Clustertool in production; and it has proven to predict the renovation potential of houses in the first use-cases. So far, we use features coming or derived from open data sources, and we experiment on using image based features which are crucial to improve the performance of the classifiers.
Creating qualitative image based features on address level is challenging for multiple reasons. During the internship you would have to explore various topics such as:
Qualitative new features would then be added to the current ones. Our innovative approach can only be successful with an optimally functioning and scalable Clustertool. In this way, you will make a lasting impact on the Dutch fossil-free renovation strategy.
With your expertise in machine learning and software engineering, you will strengthen our team of 30 experts in the field of digitalization in construction. You can learn a lot from your colleagues, for example in the field of computer vision, data science, machine learning and software development, along with gaining insight into the various aspects of digitizing and automating the built environment.
What we expect from you
First things first: you do not need to have any background in construction or sustainability to apply for this internship. Of course, if you do, that's a bonus, but surrounded by our experts, you'll learn quickly.
What else you need to bring:
What you'll get in return
You want an internship opportunity on the precursor of your career; an internship gives you an opportunity to take a good look at your prospective future employer. TNO goes a step further. It’s not just looking that interests us; you and your knowledge are essential to our innovation. That’s why we attach a great deal of value to your personal and professional development. You will, of course, be properly supervised during your work placement and be given the scope for you to get the best out of yourself.
Furthermore, we provide:
