Complex microbial Ecosystems MUltiScale modElling:
mechanistic and data driven approaches integration
Closed for Applications
Early Stage Researcher (ESR11)
PhD Fellowship in Biology driven Complexity Reduction of Individual based Models
“E-MUSE Complex microbial ecosystems multiscale modelling: mechanistic and data driven approaches integration” MSCA-ITN-2020 European Training Network
KATHOLIEKE UNIVERSITEIT LEUVEN (KUL), established in OUDE MARKT 13, LEUVEN 3000, Belgium
Gent Chemical & Biochemical Process Technology & Control (BioTec+), Ghent and Aalst Technology Campuses
Engineering Science, Bioscience Engineering, Chemical Engineering, Computer Science
You can apply for this job no later than October 15, 2021
Envisaged Job Starting Date
3 years financial support to pursue a PhD (including Living, Mobility and Family Allowance according to H2020-MSCA-ITN regulations)
ESR11 to be recruited by KU Leuven/BioTeC+ will focus on the power and limitations of two predictive microbial modelling paradigms: on the one hand Individual based Models (IbM) and on the other hand Partial Differential Equations (PDEs). In the context of multi-organism populations, Individual based Model (IbM) approaches can cope with the spatial distribution that will be useful to describe cell to cell interaction. A typical challenge is to provide a bridge between the (computationally very intensive) IbMs and population models which typically take the form of PDEs, and therefore to provide a feedback to genome scale modelling with the help of accurate spatial/temporal characterizations.
IbM model design considering complex mechanical and dynamical properties of cheese ecosystems and integrating metabolic network information at individual cell level;
IbM model reduction. IbMs will be analysed and, applying the laws of large numbers, a tentative model reduction will be achieved in order to derive equivalent meso-scale PDE systems while maintaining model accuracy at a pre-specified level;
PDE model design. Conversely to IbM reduction, starting from macroscopic population descriptions and assumptions, PDE models will be investigated, describing spatial/temporal population evolutions, i.e., taking into account convective, diffusive phenomena;
Model parameter identifiability in view of the available experimental data, including model parametric sensitivity analysis in order to detect possible over-parameterization.
In total, 4 months will be spent at Vrije Universiteit Amsterdam (VUA) in Netherlands (Systems Biology).
Enrolment in Doctoral degree
Required Education Level
We are seeking highly motivated candidates that hold a master in Mathematical/Chemical/Biological/Computer/... Engineering related subjects such as (Bio-)Process Modeling, Systems (Micro-)biology, and Applied Mathematics.
Skills / Qualifications
the candidate should be open to interdisciplinary collaboration and be interested in both fundamental and applied research.
networking and good communications skills (writing and presentation skills)
willingness to travel abroad for the purpose of research, training and dissemination.
English: B2, good oral and written communication skills in English are compulsory
The lead supervisor Prof. Jan Van Impe, the Division Head and founder of BioTeC (Chemical and Biochemical Process Technology and Control) research group at KU Leuven is also a coordinator of the European Master of Science in Food Science, Technology and Business (BIFTEC), co-funded by the Erasmus+ Programme of the European Union. J. Van Impe (co)supervised 65 PhDs and you can become part of the dynamic KU Leuven/BioTeC+ research group (6 postdocs and about 14 PhD researchers), headed by Prof. Jan F.M. Van Impe. The co-supervisors are Prof. Vasilis Valdramidis - leading a strong group in the area of food safety and processing at the Faculty of Health Sciences of Universita Ta Malta; prof. Bas Teusink – the head of the Systems Biology group at Vrije Universiteit Amsterdam and Irene Otero-Muras - currently researcher at BioProcess Engineering Group (IIM-CSIC) developing tools for Biosystems Identification, Design and Control for Synthetic and Systems Biology applications and soon she is starting a new biosystems engineering group at I2SysBio in Valencia.
Host Institution Description
The vision of BioTeC+ (Chemical & Biochemical Process Technology & Control) is to consolidate and strengthen both its international research position and its societal impact by focusing on a carefully selected number of research areas and application domains in applied chemistry/chemical and biological process engineering.
At present, these application domains can be characterized by the keywords industrial biotechnology, closing the waste/water cycle, and public health. These constitute the pillars (columns) (bio)chemical reactions & reactors, (biological) waste(-water) treatment systems, and predictive microbiology/microbial risk assessment within BioTeC’s research matrix. This broad range of application domains is supported by our long standing systemic (systems and control) approach towards applied chemistry/chemical and biological process engineering. The research areas system theory and analysis, process model identification (including optimal experimental design), process monitoring, optimization and model based control characterize the transversal rows in the research matrix. These rows constitute the longstanding fundament of BioTeC’s research covering and underpinning all application domains (pillars).
The underlying motivation is that model based solutions to chemical and biological process design, optimization and control are superior in performance and robustness as compared to plain heuristic approaches. In the case of microbial conversions for example, process optimization is aimed at by creating optimal environmental conditions for the cell. Therefore, this line of research is fully complementary to process optimization by genetically modifying the cell itself. To realize this mission, interdisciplinary research is required: both concepts and techniques from mathematical modeling and systems and control as well as detailed (micro-)biological/(bio-)chemical knowledge are essential building blocks for high performance process identification, intensification and control algorithms.
KU Leuven/BioTeC+ runs a state-of-the-art L2 accredited laboratory for experimental predictive microbiology research, as well as high-end computing facilities. Our 6 postdocs and 14 PhD researchers are involved in numerous international research projects and networks, including 5 ongoing EU projects. As a most international and inclusive team, we look forward to welcome you on our campus in the vibrant city of Gent, Belgium!
KU Leuven seeks to foster an environment where all talents can flourish, regardless of gender, age, cultural background, nationality or impairments.