Recruitment process has been sucessfully closed!
We are excited with the new recruits, selected among many, to pursue 7 doctoral theses within the project framework!
The SERENADE project involves a consortium of 5 leading European companies from Spain, Germany, Italy, and Belgium, along with 5 research universities. The consortium intends to train 7 Ph.D. researchers in building smart sustainable solutions targeting the reduction of food waste at the end of the food supply chain. These 7 multidisciplinary Ph.D. projects are grouped according to three pillars: food, sensors, and materials technologies. Funding for these projects has been provided by the EU under their competitive HORIZON-MSCA-DN-2021 (Marie Skłodowska-Curie Doctoral Networks) program under Grant Agreement No. 101072846.
The consortium invited applications for up to 7 highly motivated and talented Ph.D. candidates (Doctoral Candidates, DCs) for these fully-funded positions. Recruitment has been open until all positions were filled by begining of 2024. The target start date for the first positions was October 2023. DCs are employed full-time and based at one of 5 host companies for 18 months and at one of 4 host universities for another 18 months. They will also spend up to 5-months on secondment at partner organizations, thereby ensuring that all DCs will spend time in both academia and industry and at least in two different countries.
Below more information can be found about the 7 doctoral thesis:
DC 1: Prediction of quality and shelf life of fruits and vegetables through the modelling of the profile of headspace volatiles and the recognition of the actual physio-metabolic state
University of Zaragoza, BSH Home Appliances
The DC is working on the production of different models able to assess the current states (physicochemical, physiological, microbiological, and sensory), and their future evolution, of fruit and vegetable stored in smart fridge containers through their profile of headspace volatiles.
Specific objectives:
- To characterize the sequence of physiological and microbiological states of selected fruits and vegetables during their storage in smart fridge containers.
- To assess the effects of the main variables of the storage conditions on their timing and duration.
- To relate those states to the sensory acceptability, food quality and shelf life of the products and VOCs profile.
- To build models relating the actual profile of volatiles to the current state of the product.
- To use these models to validate sensor networks and biomaterials developed in the frame of the project to predict food current state and its future evolution.
Secondments are planned in 3S, Sirmax and Vito.
DC 2: Prediction of the quality and shelf life of cooked meals/leftovers stored in a smart fridge container through the modelling of the profile of headspace volatiles and the recognition of the actual microbiological state
University of Zaragoza, BSH Home Appliances
The DC is working on the production of different models able to assess the current states (physicochemical, physiological, microbiological, and sensory), and their future evolution, of cooked meals/leftovers stored in smart fridge containers through their profile of headspace volatiles.
Specific objectives:
- To characterize the sequence of physiological and microbiological states of selected cooked meals/leftovers during their storage in smart fridge containers.
- To assess the effects of the main variables of the storage conditions on their timing and duration.
- To relate those states to the sensory acceptability, food quality and shelf life of the products and VOCs profile.
- To build models relating the actual profile of volatiles to the current state of the product.
- To use these models to validate sensor networks and biomaterials developed in the frame of the project to predict food current state and its future evolution.
Secondments are planned in 3S, Sirmax and Vito.
DC 3: Optimization of MOS sensor performance using temperature cycled/modulated operation to evaluate the state of food decay (and forecast edibility) with artificial intelligence
University of Saarland, BSH Home Appliances
The DC is working on the development of a novel sensor system for monitoring food freshness in closed environments. The sensor system is based on metal oxide semiconductor (MOS) gas sensors run in temperature cycled operation (TCO) in order to enhance the sensitivity and selectivity of the sensors. The multivariate sensor data is evaluated by a dedicated AI model.
The project includes:
- Selection of the most suitable sensors to determine the volatile profiles and identification possible interfering gases
- Determination of preferable operation temperatures and modes for the specified volatile profiles (input from DC1 – DC2)
- Building a model/AI software to examine the current condition of the food
- Estimate a time frame of safe consumption if possible.
- Integration of impedance spectroscopy for self-monitoring of the MOS-TCCO system (input from DC5)
- Supervised testing in an application-oriented environment in collaboration with DC1 – DC2
- Validation of the sensor system
Secondments are planned in University of Zaragoza and Vito.
DC 4: Coupling of MOS sensors with a chromatographic column: Design, installation, exploring new operations and classification
University of Saarland, 3S
The DC is working on the development of a novel miniaturized gas chromatograph with a metal oxide semiconductor (MOS) gas sensor as a detector (mini-GC). The mini-GC shall be realized as a hand-held device for monitoring the freshness of food in open environments.
The project includes:
To develop a mini-GC system with MOS gas sensors as detector to track food freshness with high gas selectivity. The following objectives are sought:
- Select most suitable sensors for the determination of the volatile profiles
- Design of a measuring chamber for selected sensors
- Exploration of operation modes for peak detection with MOS sensors in a test setup
- design a solution for simple sampling and injection of food headspace
- Integration of the system (sensor and chamber, injector, and column).
- Characterization of whole setup with analytical standard mixtures
- Supervised testing in an application-oriented environment.
Secondments are planned in University of Zaragoza, BSH and Vito.
DC 5: Innovative excitation schemes for accurate food state and freshness detection using semiconducting metal oxide sensors in combination with AI methods
University of Saarland, Bosch Sensortec
The DC is working on the development of novel excitation schemes for metal oxide semiconductor (MOS) gas sensor, e.g. like impedance spectroscopy. The new frequency modulation schemes shall be implemented on a FPGA. The multivariate sensor data is evaluated by a dedicated AI model.
The project includes:
To develop a mini-GC system with MOS gas sensors as detector to track food freshness with high gas selectivity. The following objectives are sought:
- Comprehensive literature research for impedance spectroscopy method in combination with MOS sensors
- Circuit design & realization (e.g., FPGA-based) for frequency-modulated operation of MOS sensor arrays
- Gas test DOEs (both lab tests w/ indicator gas mixtures and reproducible field tests w/ food containers; including setup design and realization)
- Exploration of frequency modulation variants and benefits for food freshness detection with MOS sensors
- Developing the right AI framework and using the results for accurate food state & freshness detection
- Identifying concrete excitation schemes, to guarantee a good detection accuracy and high power-efficiency
- Validation of the sensor system
Secondments are planned in 3S, BSH and Vito.
DC 6: A compostable food container able to withstand dishwashing cycles will be prototyped by the combined development of a compostable PLA-based food-contact compound and of an innovative annealing technology based on volumetric heating
University of Padova, Sirmax
The DC is working on the development of a compostable food container able to withstand dishwashing cycles by combining a compostable PLA-based food-contact compound and an innovative annealing technology. Microwave heating will be used to promote post-molding crystallization and increase the mechanical properties of the injection-molded PLA compounds.
The project includes:
To develop and test food-contact additives for the PLA compounds that can act as energy absorbers and increase the efficiency of the annealing technologies without compromising the material compostability. The following objectives are sought:
- Comprehensive literature research to identify microwave energy absorbers additives for the PLA compounds.
- Optimization of compounding parameters to obtain an effective additive dispersion.
- Optimization of annealing parameters to achieve high and durable mechanical properties at high temperatures.
- Evaluation of end-of-life compostability
- Prototyping and validation of the compostable food container
Secondments are planned in BSH, University of Zaragoza and Vito.
DC 7: Eco-friendliness of food-grade bio-based and with dissolution purification technology recycled plastics
Galloo, VITO, KU Leuven
This PhD aims to increase the sustainability of the materials of food containers by the incorporation of polymers recycled from complex waste streams. To achieve this, an innovative recycling process will be developed, combining mechanical and chemical treatment steps, to allow selective polymer recovery while maintaining its physical-chemical characteristics. The most promising end-of life streams will first be selected and characterized, then the optimal pre-treatment by mechanical sorting will be investigated, and finally a highly selective dissolution-based approach will be developed. Process sustainability and the effectiveness of contaminant removal will be major focus points. For this, also the eco friendliness (LCA) and economic viability (LCC) of the recycled plastics will be compared to the use of virgin polymer and biobased polylactic acid.
Secondments are planned in KU Leuven and BSH.