PhD position on optimizing cooling processes and supply chains of heat-sensitive biological products by digital twins

PhD position on optimizing cooling processes and supply chains of heat-sensitive biological products by digital twins

Materials science and technology are our passion. With our cutting-edge research, Empa\’s around 1,100 employees make essential contributions to the well-being of society for a future worth living. Empa is a research institution of the ETH Domain.

Empa\’s Laboratory of Biomimetic Membranes and Textiles is a pioneer in physics-based modeling at multiple scales. We bridge the virtual to the real world by multi-parameter sensing and creating digital twins of heat-sensitive biological systems (food, humans) that can live together with their real-world counterparts. This project aims to better identify how perishable biological products react inside cold chain unit operations and to pinpoint why some products decay faster. For that purpose, we develop digital twins of the cargo, based on measured air temperature and humidity data in cold chains by commercial sensors, and deploy them in end-to-end virtual supply chains.

This project also aims to better understand the tradeoffs related to cooling technology for several use cases, for example, with smallholder farmers in the Global South. For that, detailed supply chain assessments will be performed. The work will enable us to identify better how individual perishable products react inside a cargo of millions in cold chain unit operations and to pinpoint why some products decay faster than others. This information will be used to quantify the environmental and economic impact of optimized cooling solutions and refrigerated supply chain solutions.

Your tasks

The priorities of the tasks will be flexibly decided depending on the concrete opportunities at hand after starting:

• Develop multiphysics models for the complete supply chain of selected heat-sensitive biological products. This includes hygrothermal transport in the ensemble of packed products during cooling, convective exchange with the environment, biochemical quality attribute evolution within the products, and thermally-driven damage (chilling-freezing injury).
• Use these models to build physics-based digital twins of all products in a shipment that age in-silico with the real product, end-to-end in the supply chain. Sensor data feed these digital twins. They translate these data, in a mechanistic way, to product quality attributes, such as remaining shelf life.
• Process measured sensor data of commercial cold chains, analyze data for variability, and reformat data in databases.
• Use the simulation-based approach to (1) better understand and steer refrigeration processes or packaging design by optimizing for product quality loss and waste, and (2) connect the improved quality preservation from digital twins, so extra shelf life, to economical advantages.
• Perform an end-to-end supply-chain assessment method to map tradeoffs for different cooling technologies for selected stakeholders to get a holistic view of the optimal cooling technology.
• Integrate these digital twins into other platforms, such as mobile applications.
• Extend the digital twin work for heat stress predictions of humans to assess the health and performance of humans in several situations (e.g. firefighters, who are exposed to extreme heat, or older adults who are exposed to heat stress during heat waves) by modeling the environment, clothing, and skin (and body), including convection, radiation, and conduction in materials.

Your profile

• Completed Master`s degree in mechanical engineering
• Proven experience in continuum modeling (finite element modeling, computational fluid dynamics).
• Knowledge of heat and mass transport processes in heat-sensitive materials and process optimization.
• Experience in supply chains and hygrothermal measurements is advantageous (temperature, infrared, anemometry).
• Excellent communication skills and fluency in English (both written and oral) are mandatory. Knowledge of German is considered advantageous.
• You have a flair for communicating with industrial and other partners.

Our offer

A project duration of 3 years is envisaged to carry out the above research tasks in the form of a PhD thesis. The project is supported by Empa under the supervision of Prof. Thijs Defraeye (academic supervisor). It involves a joint affiliation with ETH Zürich (D-USYS). The candidate will perform the research at Empa in St. Gallen. The desired starting date is 1st of October 2025 or upon mutual Agreement. This project is performed in close collaboration with industrial and other partners.

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