Mots-Clés
bioinformatics
population genomics
statistics
drug resistance
evolution
Description
Practical info from Pleuni Pennings
The official ad is here: https://euraxess.ec.europa.eu/jobs/468402
The postdoc position can start on the first of Nov 2026 for 23 months.
The ad says that “The net monthly salary is between €2,200 and €2,380” per month.
How to apply?
Send a 1-2 page cover letter that describes your motivation for the project and your experience in bioinformatics, your CV, a paper (or draft) written by you, and names and email addresses for three references to pleuni.pennings@umontpellier.fr. Only pdf’s please!
The deadline is Oct 25th but I will start reading applications on the 10th. Feel free to let me know ahead if you are planning to apply.
What is the project?
The goal of the project is to uncover the rules that determine the dynamics of drug resistance in different pathogens. I use modeling techniques from ecology, evolution and epidemiology and publicly available data from surveillance programs and genomic databases. I work on various pathogens (HIV, E. coli and P. falciparum) to be able to compare and contrast. The postdoc will work on two of the three sub projects.
Sub project 1: Resistance to antimalarials in P. falciparum
This subproject focuses on resistance to mefloquine which is caused by a gene amplification of the Pfmdr-1 gene which is known to occur recurrently. However, despite the high rate of de novo evolution of resistance, resistance had not reached fixation in the population. The goal of this subproject is to determine the fitness cost of the amplification and determine whether this cost explains why it is not fixed. We will use publicly available sequencing data, determine amplification breakpoints to identify independently evolved resistance alleles and infer the fitness cost of carrying the resistance alleles using phylogenetic approaches.
Sub project 2. Diversity of resistance in E. coli populations
It is known that for many drug-bacteria pairs, consumption levels of drugs correlate with resistance levels. We hypothesize that higher levels of resistance in countries with higher treatment levels are caused by more origins of resistant strains. We plan to test this hypothesis by determining diversity of resistant bacterial strains in different countries and at different time points using subsets of the Enterobase database which contains several hundred thousand E. coli genomes.
Sub project 3: Reusable machine learning models to predict drug resistance
Machine learning models to predict antibiotic resistance phenotypes are usually specific to one particular dataset. This limits their practical usefulness. We propose here to align genomes to a standardized reference pan-genome to capture information on SNPs and gene presence-absence in a standardized way. This means that a model that was trained on one dataset can be tested on new genomic data which will allow us to determine how generalizable the models are.
Related work
I have done a lot of work on drug resistance evolution. Have a look at my publications here.
Here is a short video about a recent paper related to the current project:
https://vimeo.com/1113132836?fl=pl&fe=vl
Why this is a great opportunity
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Because drug resistance evolution is a cool & important topic.
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Because Montpellier is a great city (if you don’t mind the heat in the summer). It has good & free public transport (though today the tram didn’t go because of a demonstration / it’s France!), reasonable bikability, more affordable than Amsterdam, Paris, San Francisco, with the beach nearby and fast trains to Paris and from there to London and Amsterdam.
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Because you’ll be part of an friendly, international team with PhD students, postdocs and researchers from many different countries. The EEC team consists of around 20 people with 8 different nationalities.
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I have lots of experience in bridging evolutionary biology and public health, I have published many times with students and postdocs, and I fully expect that the postdoc I hire will get a really nice publication (or 2) out of this. Because I have a research-only position I will have sufficient time to dedicate to supporting you / collaborating with you.
Skills/Qualifications
I am looking for a curious and motivated candidate with a PhD in biology or bioinformatics with skills in bioinformatics and sequence analysis and experience coding in Python or R or related languages. Other useful (not required) skills and interests would be modeling, simulations, evolutionary / population genetics, statistics, writing, reading primary literature, and public health.