Today, fresh produce is highly unsustainable: 33% of fresh fruit and vegetables is lost or wasted. Would you like to help combat this problem by contributing to the development of the first automated multispecies trace gas sensor, allowing the detection of volatile gases that indicate ripening, fermentation, damage or rotting of produce? Then you have a part to play as a postdoctoral researcher.
You will be part of the Life Science Trace Detection Laboratory at Radboud University, where you will work on the H2020 MAX-FRESH project , developing the world's first automated commercial multi-species trace gas analyser based on mid-infrared absorption spectroscopy.
You will be involved in the development of the gas analyser, focusing on the measurement of volatile organic compounds emitted from fruits and vegetables during long-term storage. These compounds are indicators of biochemical processes such as ripening, fermentation, damage, or rotting. Once unfavourable conditions are detected at early stages, the analyser will provide automated alerts to enable timely and effective interventions, allowing reducing storage losses by 50%, extending storage life by 20%, and reducing post-harvest chemical treatments by 50%. The consortium consists of Radboud University and three industry partners (NKTP, Denmark; Senseair, Sweden; STOREX, Belgium). Prototypes were previously built at TRL6, and the systems were tested and validated for the final application. In the current project, we aim to reach TRL9, meaning that the analyser will be ready for scale-up and commercial exploitation by the end of the project. Your role and responsibility will include:
• System design and assembly of various components and modules of the analyser, such as the spectrometer and optics, temperature control units, and gas handling system.
• Laboratory and field measurements to assess system performance and validate functionalities.
• A minimum of 10% travel (mostly within the Netherlands for system installation, maintenance and support).
• Data acquisition and data analysis.
• Assisting to improve the integrated analyser software package (LabVIEW/Python).
• Contributing to the writing of conference papers and articles in scientific journals.
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