Mots-Clés

Engineering Science, Bioscience Engineering, Chemical Engineering, Computer Science

Description

Project

H2020-MSCA-ITN E-MUSE: Complex microbial Ecosystems MUltiScale modElling: mechanistic and data driven approaches integration https://www.itn-emuse.com/

The E-MUSE training programme aims at developing young researchers’ skills at the interface between artificial intelligence and life sciences. The challenge is to acquire a shared language bridging life science questions and original modelling approaches. The research programme of the E-MUSE network is to develop innovative modelling methodologies to understand a complex microbial ecosystem and identify levers to control and/or predict its evolution. To deal with biological complexity, biologists, mathematicians, and computer scientists have to work together to develop innovative methodologies. An important complexity of this domain originates from scales and dynamics issues, ranging from local kinetics at the level of the cell to emerging macroscopic properties of the biological system. The development of high throughput techniques provides more and more large datasets, but knowledge is not easily inferred from this huge amount of data and multiscale dynamics are still incompletely characterised and predicted. E-MUSE’s transdisciplinary network gathers academic and industrial partners to equip (15) Early Stage Researchers (ESRs) with scientific, research and transferable skills to become leaders in academic research or industry. They will be at the cutting edge of the modelling methodologies that we apply to model structural and dynamic features of microbial communities, to identify key processes and biomarkers for specific applications.

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.

Expected results include:

• 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,ng 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.

Profile

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.

The candidate should be open to interdisciplinary collaboration and be interested in both fundamental and applied research.

Specific eligibility criteria for H2020-MSCA-ITN networks:

Early-stage researchers (ESRs) are those who are, at the time of recruitment by the host, in the first four years (full-time equivalent) of their research careers and have not been awarded a doctoral degree. This is measured from the date when they obtained the degree which formally entitles them to embark on a doctorate, either in the country in which the degree was obtained or in the country in which the research training is provided, irrespective of whether or not a doctorate was envisaged. The applicants cannot already hold a PhD. Researchers are required to undertake trans-national mobility (i.e., move from one country to another) when taking up the appointment. At the time of selection by the host organisation, researchers must not have resided or carried out their main activity (work, studies, etc.) in the country of their host organisation for more than 12 months in the 3 years immediately prior to their recruitment. Short stays, such as holidays, are not taken into account. ITN fellows (ESRs) must demonstrate that their ability to understand and express themselves in both written and spoken English is sufficiently high for them to derive the full benefit from the network training. Non-native English speakers are required to provide evidence of English language competency before the appointment is made.

Offer

3 years financial support to pursue a PhD (including Living, Mobility and Family Allowance according to H2020-MSCA-ITN regulations);

The H2020-MSCA-ITN E-MUSE training network of 15 PhD students offers a unique environment for international academic-industrial collaboration;

Being part of the dynamic KU Leuven/BioTeC+ research group (6 postdocs and about 14 PhD researchers), headed by Prof. Jan F.M. Van Impe;

Living in the beautiful and vibrant city of Gent, situated in the heart of Europe;

Internship/Secondment within the E-MUSE network: 4 months at Vrije Universiteit Amsterdam, The Netherlands (Systems Biology).