The lab: Stroustrup group

Lab's research themes:

Our group studies the complex causal pathways through which genes, drugs, stress, and diet influence aging. We combine molecular genetics and functional genomics approaches with quantitative modelling, drawing on concepts from statistical physics and complex systems theory. In this way, we develop and apply new, interdisciplinary approaches to study how our genes, environment, and random chance intersect to determine how and how fast we age.

Merits of the lab:

The Dynamics of living systems Group is part of the EMBL/CRG Systems Biology Unit at the Centre for Genomic Regulation. Broadly speaking, we study the way in which molecular mechanisms determine the timing of physiologic events during aging. We do this with an interdisciplinary mix of molecular genetics, complex systems perspectives, synthetic biology, statistics, modelling, and math. We focus on the nematode C. elegans as a fast-aging, genetically tractable model system.
We also develop and maintain an imaging technology named the Lifespan Machine:
The Lifespan Machine is an automated imaging platform that combines modified flatbed scanners with custom image processing and data validation software. The technology automates the collection of high-accuracy, large-population, nematode survival data. It has been used for a variety of purposes, including studying the effect of genes, diets, drugs and environmental factors on lifespan, stress resistance, and pathogen resistance.
Some relevant publications:
Natasha Oswal, Olivier M.F. Martin, Sofia Stroustrup, Monika Anna Matusiak Bruckner, Nicholas Stroustrup. A Hierarchical Process Model Links Behavioral Aging and Lifespan in C. elegans. Bioarxiv 2021
Nicholas Stroustrup, Bryne E Ulmschneider, Zachary M Nash, Isaac F López-Moyado, Javier Apfeld, Walter Fontana. The C. elegans Lifespan Machine. Nature Methods 2013 10 665–670 (2013)

Country: Spain
Supervisor: Nicholas Stroustrup

The position

What’s the main purpose of our research?

We have developed functional genomics and modelling approaches to identify aspects of cell biology that correlate with remaining lifespan across a variety of timescales.

How we will do it?

We are looking for a candidate who can develop their existing quantitative bioinformatics skills to exploit the conservation of these mechanisms between C. elegans and humans to understand their impact on human health.

Methodologically, we pursue a mixture of bulk, single-individual, and single-cell transcriptomics, CRISPR genome editing (in particular, developing constructs that allow us to precisely modulate aging in vivo),  C. elegans genetics, high-throughput imaging, fluorescent imaging, statistical and complex-systems modelling, machine learning, and math.

Why is this important?

In our aging society, it is crucial to better understand the molecular origins of age-associated diseases, and distinguish between systemic causes and organ-specific consequences of the aging process.

Who is a good fit for the project?

We look for an enthusiastic candidate that has interest in:



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