We develop coatings that exhibit excellent optical, chemical, and physical properties but we are also aiming at developing our own methods to measure the exact light conditions in greenhouses in an affordable way for most growers. We are already have a concept design about how we plan on achieving it but we are on the lookout for someone with good programming and lab skills to help us build and test the first prototypes.

We are a technology company from Delft (NL), engineering coating, solar and sensor solutions for the global energy transition. Across all these solutions, we consistently aim to change the perspective on how current materials are used and implemented, as well as challenging the system innovation behind them.

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Ben je benieuwd hoe je de juiste klant met de juiste boodschap bereikt? Of hoe je een effectief leadgeneratieplan opstelt en uitvoert? In deze rol gebruik je je kennis en ervaring om een leadgeneratieproces vorm te geven en de marketingcampagne uit te voeren om de juiste klanten te targeten.

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Ben jij iemand die graag opvolgt en klanten ondersteunt? En word je enthousiast van het idee om het toepassen van onze duurzame diffuse PAR+ coating telkens weer tot een succes te maken? In deze rol help je om klanttevredenheid een trots onderdeel van ons proces te maken en zorg je tegelijkertijd voor duurzaam succes op de lange termijn.

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We're looking for passionate talent to strengthen our lively team! Do you have what it takes? 

FOTONIQ has been exploring different definitions of RTR. This parameter includes both temporal as well as spatial variation, being calculated using local and instantaneous measurements, instead of a single daily average for the entire greenhouse.

This MSc thesis project explores how plant physiology influences leaf reflectivity—an important factor for accurate light measurements. By understanding how leaf reflectance changes with growth and environment, you’ll help improve lighting strategies, boost energy efficiency, and support next-generation greenhouse innovation.

This MSc thesis project focuses on estimating key leaf traits—such as spectral reflectivity and spatial distribution—directly from camera images, reducing the need for manual measurements. By combining image analysis with environmental data, you’ll explore how to make PAR estimation faster, more accurate, and more scalable.