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Description
To provide students with skills in advanced modelling, optimisation and statistical techniques such that they are adequately equipped to address problems related to evaluating the cost-effectiveness and robustness of alternative bioprocess design strategies.
Upon completion of the course, a student should be able to:
- Use a set of approaches such as discrete-event simulation, dynamic simulation, Monte Carlo simulation and linear and mixed-integer programming to address bioprocess challenges
- Perform multi-variate data analysis to derive insights from complex datasets
- Formulate decision problems related with bioprocessing design in a structured way and select appropriate methods to solve them
- Build simulation models, optimise key decision variables and critically analyse output results
- Conduct advanced research in Bioprocess Systems Engineering
- Take the acquired expertise into industry to work as developers of simulation/optimisation/process economics models in real biomanufacturing companies
- Improve Matlab proficient such as modifying scripts and running functions to solve bioprocess problems
Module deliveries for 2024/25 academic year
Last updated
This module description was last updated on 8th April 2024.
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