PhD position: Data-driven discovery of models to describe cell cycle dynamics using machine learning techniques

Updated: about 1 month ago
Deadline: 13 Sep 2021

(ref. BAP-2021-631)

Laatst aangepast : 29/07/2021

The Laboratory of Dynamics in Biological Systems at the KU Leuven aims at understanding how networks of interacting genes, RNAs, and proteins can collectively regulate biological processes in space and time. Our present focus lies on the coordination of cell division. We combine a theoretical approach; such as computational modeling, and theory of complex systems and nonlinear dynamics; with molecular and cellular experiments using Xenopus frogs, zebrafish, and cell cultures. For more information, see www.gelenslab.org.


Project

The cell cycle is an essential process in all animals, and defects in this process can lead to devastating diseases such as cancer. In our lab, we use cell-free extracts made from frog eggs to create an artificial cellular environment in microfluidic devices. We controllably perturb these artificial cells and measure their dynamical behavior using time-lapse fluorescence microscopy. This approach allows us to generate large amounts of data on how cell cycle processes are dynamically regulated in space and time. 

In this project, the student will use these time series data containing spatiotemporal dynamics to apply recently developed machine learning techniques to discover underlying biological interactions and/or governing equations. The uncovered (partial) differential equations will then be analyzed in depth using the theory of nonlinear dynamical systems. This analysis will trigger new experiments to test the developed theoretical framework. 

The student will interact synergistically with experimentalists, theorists, and engineers. The interdisciplinary approach will lead to new insights into how fundamental biological processes, i.e. the progression through the life cycle of the cell, are regulated in space and time.

The position is available immediately and applications will be considered until the position is filled.


Profile

- You have (or are near completion of) a MSc degree in physics, mathematics, or (bio-) engineering

- You are ambitious, motivated, creative, organized, practically skillful and result-oriented

- You can work independently as well as in a team

- You have good communication skills and a good knowledge of English, both spoken and written

- You have a strong interest in the cell cycle and/or dynamical systems biology

- You have experience with machine learning, nonlinear dynamical systems, and/or bifurcation theory 


Offer

We offer a doctoral position in a stimulating, interdisciplinary environment and scientific development opportunities in an international and dynamic team. You will have access to state-of-the-art research facilities and will be registered in a specific program of the doctoral school. You will be supervised by well-trained scientists and receive thorough training in conducting research, presentations and writing.


Interested?

For more information please contact Prof. dr. Lendert Gelens, tel.: +32 16 37 42 88, mail: lendert.gelens@kuleuven.be.


KU Leuven seeks to foster an environment where all talents can flourish, regardless of gender, age, cultural background, nationality or impairments. If you have any questions relating to accessibility or support, please contact us at diversiteit.HR@kuleuven.be.


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