Postdoc: Machine learning for elucidating timing mechanisms in C. elegans development

How timing of development is controlled remains one of biology’s most enduring mysteries. For instance, how does the human body know to enter puberty more than ten years after its birth? To study developmental timing in the nematode worm C. elegans, our group has developed a microscopy approach to make time-lapse movies of the dynamics of cells in time, inside freely moving and growing worms, as they develop from hatchlings to adults (Gritti et al., 2016, Nature Comm.) Such movies make it possible for the first time to systematically measure timing of cellular events, such as cell divisions (Filina et al., 2020, Biorxiv), and uncover timing errors in mutants known to impact developmental timing. However, a key obstacle is extracting the timing of cellular events from these time-lapse movies at sufficiently high throughput.

Goal of the project
You will adapt cell-tracking techniques, based on convolutional neural networks, that we previously developed in our group (Kok et al., 2020, PLOS One), to automatically track the movements and divisions of cells inside the growing and deforming bodies of individual worms. You will use this approach to measure (variability in) timing of cell divisions and movements of different cell types and synchronization of this timing between different tissues, and study how this is changed in timing mutants. Based on the candidate’s background, the project could also involve C. elegans experiments and microscopy imaging, or focus exclusively on analysis of data collected by other researchers in the group.

About the group

The ‘Quantitative Developmental Biology’ research group uses a quantitative, physics-inspired approach to study problems in developmental biology, focusing both on the small nematode C. elegans and intestinal organoids. The aim of the research is to elucidate how living organisms reliably build their bodies, maintain their tissues or respond to their environment despite the considerable underlying variability on the molecular level. 

Qualifications

You need to meet the requirements for a doctors-degree and must have research experience in a non-Dutch academic environment. We seek candidates with a background in bioinformatics, (theoretical) physics or engineering. Prior experience with (microscopy) image analysis, machine learning and neural networks is preferred.

Terms of employment

The position is intended as full-time (40 hours / week, 12 months / year) appointment in the service of the Netherlands Foundation of Scientific Research Institutes (NWO-I) for the duration of two years, with a salary in scale 10 (CAO-OI) and a range of employment benefits. AMOLF assists any new foreign Postdoc with housing and visa applications and compensates their transport costs and furnishing expenses.

Contact info

Prof.dr. Jeroen van Zon
Group leader Quantitative Developmental Biology
E-mail: J.v.Zon@amolf.nl 
Phone: +31 (0)20-754 7100

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