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Marie-Curie funded 3-year PhD offer at LIRMM

A new job offer

7 min read job

We are delighted to offer a new PhD position at the LIRMM CNRS. The PhD is co-supervised by Anne-Muriel Chifolleau and myself. Details below. Contact: eric.rivals_at_lirmm.fr, anne-muriel.arigon_at_lirmm.fr

Context of the European Doctoral Network

PhD Offer in Montpellier, South of France

  • Within the doctoral network EURECA, the LIRMM / CNRS is offering a 3-year PhD position in Bioinformatics / Computer science with applications in molecular biology of cancer. The candidate will enroll in the I2S doctoral school of Montpellier University.

  • Institute and location of work: LIRMM is the unique joint research institute from CNRS and Montpellier University with research dedicated to Computer Science, Microelectronics, and Robotics of Montpellier. The PhD candidate will join the team Methods and Algorithms for Bioinformatics (MAB).

  • Supervision:

    • Dr Eric Rivals, HdR, (LIRMM), CNRS Research Director in computer science and bioinformatics (web https://www.lirmm.fr/~rivals/).
    • Dr Anne-Muriel Chifolleau (LIRMM), associate professor in computer science and bioinformatics at Montpellier Univ., does her research at the LIRMM (web https://www.lirmm.fr/~arigon/)

  • Collaboration: our group has a long-term collaboration with the group of Alex David, at the Institute for Cancer Research of Montpellier (IRCM) on chemical modifications of RNAs (aka epitranscriptomics) in cancer, and especially of an aggressive brain cancer called glioblastoma. We have jointly published several articles and a patent on tumor characterization related to our common research results.

Research topics and questions

General overview: RNA, epitranscriptomics, and cancer

For over 50 years it has been known that RNA is extensively “decorated” with chemical modifications. Their variety and number (over 100 known so far) are larger than the modifications known in DNA and proteins. RNA modifications remained poorly studied until recently. Technological improvements of the last decade now allow the high-throughput detection of RNA modifications, and the dissection of the proteins that “write”, “read” and “erase” them on the RNA molecules. This led to the ground-breaking discovery of a vast and highly dynamic layer of RNA modifications that play a role in all aspects of RNA life: from transcription, to splicing, folding, and translation into proteins. RNA modifications are thus important players in the process of gene expression. The study of RNA modifications and their function is now referred to as Epitranscriptomics.

It became clear that RNA modifications impact the turnover, translation and function of RNAs, altering gene expression and ultimately re-programming basic cellular circuits. Consequently, pathological changes in the epitranscriptome were associated with each of the cancer hallmarks and are now seen as an independent mode of “non-mutational epigenetic reprogramming”. Importantly, RNA modifications are detected in body fluids as cell-free RNA or in extracellular vesicles. These first findings show that the epitranscriptome can offer new biological insights and novel paths for cancer detection and treatment.

Despite our progress in understanding the cancer epitranscriptome, the direct links between pro- or anti-oncogenic properties of RNA modifications, their effector proteins and their orchestrated function in cancer onset and progression largely remain to be established.

EURECA offers a comprehensive approach towards understanding the biology, function and clinical relevance of RNA modifications aiming to discover new therapeutic strategies, formulations and biomarkers for cancer diagnosis and treatment. It is centered on two research and educational questions:

  1. How can we advance our understanding of the cancer epitranscriptome through the integration of cutting-edge technologies and advanced computation? And
  2. How do we refine and advance the detection and molecular manipulation of RNA-modifications to harness their potential as biomarkers and therapeutics, meeting the growing need for improved cancer diagnosis and treatment?

PhD project at the LIRMM.

  1. The candidate will participate to a on-going project to study how a profile of RNA modifications measured in blood biopsy can help predict glioma at different stages of this brain cancer, as well as the evolution of the tumor. This part of the project involves designing, developping, and running machine learning algorithms and approaches to exploit vectors of RNA modification quantities observed in patients. The measurements are performed by our local partners (Alex David IRCM, Christophe Hirtz PPC/CHU Montpellier) in a unique and local mass spectrometry platform that has developed special procedures for measurements in RNAs.

  2. The second part of the project deals with bioinformatics approaches to detect and study the role mutations in translation of RNA sequences, and their correlation with RNA modifications. The idea is to analyze transcriptome and translatome data to see determine which DNA mutations are transcribed and then translated, and which are not translated. Only mutations located in RNAs that are translated have an impact on the produced proteins. Others mutations don’t. It is known that translation varies with physiological conditions and that ribosomes can select or discard certains RNAs. Translatome of cancer cells have been produced via high throughput sequencing and generate libraries similar to RNA-seq, except that these are restricted to RNA sequences that have been translated. The goal is to develop computational algorithms and tools to analyse such sequencing data, to predict translated mutations and their potential effect on the fate of an RNA. Once pools of mutations have been detected, it is interesting to correlate them with locations of epitranscriptomic modifications, to seek potential functional interactions. This part of the work requires knowledge in and interest for algorithms for high throughput sequence analysis, in data structures for sequence data, and in processing of deep sequencing data (see the book of Enno Ohlebusch, entitled “Bioinformatics Algorithms”, 2013, available at: https://www.uni-ulm.de/in/theo/m/ohlebusch/ or the book “Genome-Scale Algorithm Design” by Makinen et al, 2nd edition https://www.genome-scale.info/). The candidate will develop efficient programs that implement the designed algorithms, and run computational analyses. The results can be confronted to knowledge databases to cancer genes.

Application and important criteria for candidates

Mobility rule and work abroad

The rules for Doctoral Network funded by Horizon Europe require that the candidate has not been living too long in France over the last 36 months. This is the Mobility Rule (see below). Mobility rule: researchers must not have resided or carried out their main activity (work, studies, etc.) in the country of the recruiting beneficiary for more than 12 months in the 36 months immediately before their date of recruitment.

Moreover, during the doctoral period, the candidate will work in another institute (beneficiary) of EURECA in one or two secondment periods of at least one month each.

Required:

  • a master degree or an engineering degree in computer science or in computational bioinformatics with strong emphasis on algorithms
  • ability to structured programming in C++ and Python
  • knowledge of linux / unix operating system
  • fluent knowledge of spoken and written English
  • fundamental knowlegde of machine learning (and statistics)
  • good level of scientific reasoning
  • ability to work hard

Highly welcome:

  • knowledge of French or interest in learning French
  • interest in biology and applications to medical sciences
  • curiosity, open mindedness, interdisciplinary work and discussions
  • wish to travel and work in other environments
  • clarity and good level in writing

Offer and advantages

  • 3-year contract at CNRS
  • Healthcare and full social security included
  • Interdisciplinary team in a renowned institute
  • High level scientific environment of Montpellier with many opportunities for collaborations,
  • Integration in a Marie-Curie doctoral network.

Application file

  • Vitae (CV)
  • A letter explaining your interest for the topic, your skills, and the reasons why you want to engage in a PhD project
  • Short description of master project and other projects, including dates, scientific question, obtained results and implementations (if exist), institute, location, name and contact of advisors/supervisors, related publications
  • Letters of references by former advisors and their full contact (name, institute, address, email, webpage)
job offer
Eric Rivals
CNRS Research Director in Computer Science and Bioinformatics

My research interests include string algorithms, bioinformatics, genomics.