Postdoctoral Research Visit F/M Individual-based Modeling of Coupled Single-cell and Population Processes
il y a 2 semaines
Context and Advantages of the Position
Inria is the French national institute for research in computer science, control, and applied mathematics promoting scientific excellence and technology transfer. Our research topics are at the intersection of mathematical biology, statistics, control engineering, and statistical physics applied to problems in biology.
Research Project
This research project aims to better understand the mechanisms related to gene expression and plasmid copy number fluctuations in a cell population with application to synthetic biology.
Modelling gene expression has been the subject of much interest in the literature. The models proposed are generally single-cell, and based on the central dogma of molecular biology, which describes a simplified scheme whereby instructions on DNA are transcribed into messenger RNA, which in turn is translated into proteins. In this scale, the environment is often assumed to be highly invariant and the number of molecules for each protein is small and therefore subject to considerable stochasticity. These numbers of molecules are modelled using continuous-time Markov chains (CTMC). In the scale of the demography, this individual dynamics becomes rapid and can be approximated by continuous models like ODEs. In addition, it becomes essential to take into account the unequal sharing of all this molecular content at the time of cell division. This mechanism is well known to enhance the heterogeneity of gene expression at the population level. How to develop models that capture all these aspects while remaining analytically or numerically tractable is an open research question and will be the focus of this project.
Main Activities
- Develop an individual-based modeling framework that can be used to understand coupled single-cell and population processes.
- Develop approaches to mathematically analyse individual-based models and to numerically simulate them.
- Make use of single-cell microscopy data of our collaborators to parameterize a model of a synthetic gene circuit in bacteria.
- Use the model to study how the burden for cells created by the synthetic gene circuit affects emerging population growth rates.
Required Skills
- Strong programming and mathematics skills.
- Prior experience with single-cell microscopy data.
- Prior experience with stochastic individual-based models.
Benefits
- Subsidized meals
- Partial reimbursement of public transport costs
- Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.)
- Possibility of teleworking and flexible organization of working hours
- Professional equipment available (videoconferencing, loan of computer equipment, etc.)
- Social, cultural and sports events and activities
- Access to vocational training
- Social security coverage
Remuneration
According to profile
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