Artificial intelligence (AI) promises great advances for the modeling and operation of chemical industrial processes. We are seeking a highly motivated Postdoc to work on AI methods and applications for digital twins of chemical industrial processes.
In this postdoc project, you will develop novel tools for the operation of chemical processes with AI. The project is the beginning of a long-term collaboration with industrial partners that provide operational data and process information. Also, you will get access to a pilot plant that will facilitate the development of AI methods and new inline sensor development. You will use the operational data and process topology information to develop a digital twin for optimal operation. The process of interest is a spray drying process. Spray drying is one of the most applied methods in the food, chemical, and pharmaceutical industries to continuously transform liquid-solid mixtures (slurries) into solid particles.
In the project, you will combine chemical engineering knowledge with data-driven approaches in an effective way. The methods that you will develop and apply can potentially include hybrid modeling, graph neural networks (GNNs), physics-informed neural networks (PINNs), recurrent neural networks (e.g., LSTMs), semantic technologies, and much more. We are happy to provide you with more technical details about our vision in a personal interview. We also expect you to develop new or used already available sensors, to test, to improve to facilitate the data collection, using a pilot spray drier
We support you to become a future leader in AI in chemical engineering. This project will prepare you for a future career in academia and industry. You will be responsible for the full project. This includes scientific research (e.g., method development and application) as well as project organization and collaboration with the industry. You will supervise a team of graduate students and potentially co-supervise PhDs. Theirs, but also your work will be divided over practical as well as computational work at the university as well as at the industrial partner. Moreover, you will be involved in teaching activities (e.g., a course on AI in chemical engineering) and funding acquisition. We facilitate collaborations and provide many opportunities to connect to the academic and industry communities. Finally, your work will contribute to the transition to sustainable chemical systems and you will have the opportunity to work in an interdisciplinary environment and interact with world-class collaborators.