10. Data Science and Computational Science for Sustainable Processes and Materials – 4CBLW00-10

Are you looking for a multidisciplinary CBL project at the intersection of data science, computational science, chemical engineering and chemistry? Look no further! Your multidisciplinary project focuses on data-driven insights and computational intelligence applied to complex mixtures found in continuously operated reactors. These reactors produce high-end materials with a strong emphasis on sustainability. By leveraging big data and machine learning techniques, we aim to revolutionize the way we design and optimize processes that contribute to sustainable materials production, addressing global challenges such as climate change and resource scarcity. As a collaborator you will have the opportunity to either engage in hands-on research , and/or source a data set onto which you unleash your tools that make use of artificial neural networks. You may find data-sets obtained via infra-red spectroscopy or mass spectrometry are especially suited to push data analysis on mixtures from a linear approach using matrix manipulations towards an intelligent approach in Python code. Your aim is to deliver a predictive tool  able to deal with chemical bonding effects such as adducts, solvation and hydrogen bonding. Don’t miss this opportunity to make a real impact! Join us in unraveling the mysteries of complex mixtures and advancing sustainable materials for a better world.