Dear colleagues,
my group at the University of Edinburgh is looking to fill the following position:
Postdoc in Data-driven Bioprocess Identification and Control. As the recent success of mRNA vaccines suggests, biomanufacturing holds the key to build a more resilient/sustainable future for our society. Yet, current industrial bioprocesses ignore host cell physiology: the most advanced Quality by Design and Process Analytical Testing frameworks still rely on macro variables, like Temperature, dO2, PH etc, to monitor and control bioproduction. As such variables are “information proxies” of cellular state, when their analysis suggests that production is diverging from the nominal operating behaviour, it might be already too late to correct the underlying abnormal physiological process. In this role you will have the opportunity to combine Scientific Machine Learning, Constraint-Based Modelling and Optimal Control principles to build a new generation of hybrid biological/digital twins of biomanufacturing processes, so called “cybergenetic twins”.
The ideal candidate for this post is a recent PhD graduate in AI/ML with a keen interest for dynamical systems modelling and control, or a control engineer with experience in AI/ML. Experience with the SciML.jl ecosystem in Julia is a plus.
Note: This project is uniquely suited for an entrepreneurially minded individual as there is an opportunity to spin out a new venture and become a startup founder.
This appointment is for a maximum of 12 months.
Deadline: 4th April 2023 at 12 PM
Apply here
Please, feel free to share with prospective candidates. Inquiries should be directed to filippo.menolascina@ed.ac.uk.
