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Job Description

The Institute for Functional Intelligent Materials (I-FIM) is seeking a researcher to investigate the application of scientific machine learning algorithms to develop an equation of state for dynamical systems out of equilibrium, with a focus on polymers under elongational flow. The role involves analysing large datasets from simulations and experiments to uncover patterns that traditional models may miss, aiming to enhance predictive capabilities for polymer behaviour. The work will be undertaken in collaboration with experts in algorithm development and experimental data collection and analysis. Additionally, the researcher will study the extension of developed framework to model multi-pendulum systems, exploring complex dynamics relevant to robotics and climate science. Findings will be disseminated through peer-reviewed journals, and the developed code will be made publicly available on GitHub.

Job Requirements

• Development of in the loop optimisation processes
• Ability to develop custom or apply state-of-the-art computer vision algorithms (CNN, AE, etc)
• Data cleaning, augmentation and dimension reduction
• Ability to work with common Python ML libraries (scikit-learn, tensorflow 1 & 2, pytorch), develop custom neural networks and implement classification and regression algorithms
• Interdisciplinary collaboration with researchers and scientists from different academic backgrounds
• Experience working in organic laboratories
• Knowledge of working with microfluidics platforms