Motivation and Goals

The ability to accurately and automatically control biotechnological processes at their optimal state accurately and automatically is of considerable interest to many biotech-industries, since it can enable them to reduce their production costs, while, at the same time, maintaining the quality of the target products. However, the highly dynamic and non-linear nature of bioprocesses poses great difficulties to bioprocess monitoring and bioprocess control approaches. Prerequisite for successful process control is the control of process parameters including cell specific growth, nutrient conversion as well as production rates using digital twins. Digital twins are virtual replica of the bioprocess and are based on hybrid modelling the relationships between inputs, process parameters and output, such as quality attributes and productivity.

We are in the comfortable position that we got granted multiple prestigious projects, in which we can develop and deploy digital twins targeting biopharmaceutical products.

In close cooperation with the project partners, this post doc position comprises to:

  • Lead and guide a team of bioprocess engineers, biotechnologists and data scientists to establish a generic approach for digital twin development, adaption and deployment in optimum and robust control of complex biopharmaceutical processes
  • Develop workflows for efficient hybrid model generation and lifecycling
  • Implement different process digital twin and control strategies and run them in real-time in our sophisticated bioprocess environment using selected PAT tools.
  • Verify them on different industrially relevant large molecule biopharmaceutical production platforms
  • Take over the operative project responsibility for at least two already granted projects including keeping timelines of deliverables, communication to project partners etc.
  • Collaborate with the internal team lead on PAT and multi variate data analysis

Requirements

  • PhD in Bioprocess Technology, Biotechnology, Electrical Engineering, Chemical Engineering or similar
  • Lab experience in bioprocessing
  • Knowledge in developing models and used to handle large data sets using data science tools
  • Experience in numerical programming skills such as Matlab® and Python®
  • A superior command of English, work experience abroad is an additional asset
  • You should be accustomed to networked critical analytical thinking, scientifically interested and able to work in a team
  • Interested to take over team lead responsibility

Opportunities

  • Work in a multidisciplinary Team
  • Connect with industry and learn their language and thinking
  • Intensification skills in highly requested field of process system engineering and data science
  • Possibility to guide PhD projects, lead a research team and take the possibility to deeper collaborate with other team members inside and outside of the organization

Time-frame & Salary

  • This position starts on July 1st 2022 and is scheduled for at least 3 years
  • The monthly minimum wage is currently € 4.061,50 (14x per year), before tax, at a 40h/week employment
  • The TU Wien aims to increase the proportion of women and encourages qualified women to apply

We are looking forward to your application!

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