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Project Description

The PhD student will work on the impact of the microenvironment of the human gut on colonisation and virulence of enteric bacterial pathogens (EHEC). In this project, you will use a highly physiological human colon model, combining patient-derived colonic organoids with organ-on-chip (OoC) and enabling to modulate the key gut environmental cues: mechanical stimulation (peristalsis and shear stress) and microbiota metabolites. Using several EHEC strains based on their differences in adhesins or Type IV pili, you will help to characterize the colonization, adhesion of these variants, and the consequences of the gut environmental cues on the EHEC virulence.

The work is in close collaboration with other groups in the network interested in host cell receptors and in anti-adhesion drug development. The position thus offers the opportunity of internships with both academic and industrial partners.

Methods will include the generation of human colonic organoids, barrier maturation in OoC, infection assays in OoC modulating mechanical forces and microbiota metabolites, live and fixed imaging quantifying the bacterial adhesion and colonization, CFU counting, barrier leakage assays, immunofluorescence and RTqPCR analysing the downstream impact of infections on the colonic barriers.

Mandatory requirements

The candidate must have:

• A Master’s degree or equivalent in Cell Biology, Microbiology or related fields at the time of admittance to the programme

• Documented experience in at least one of the following areas: Cell biology, Organoids, Cell-culture based infection assays, Live and fixed fluorescence imaging, Microbiology

Desirable qualifications

In addition, it is an advantage if the candidate has:

• A good theoretical understanding of infection biology

• A good theoretical understanding of in organ-on-chip technology

• Documented experience with quantitative image analysis

Personal skills:

We are an international team of researchers from very different scientific and cultural backgrounds. Our colleagues should have:

• Good language and communication skills

• The ability to work in interdisciplinary teams

• The ability to work independently on complex projects (from planning and execution to results presentation)

Qualification requirements: In addition to the eligibility criteria (see below in "How to Apply"), candidates admitted to the PhD programme at the Institut Pasteur will be affiliated with the Paris-Cité University under the doctoral school MTCI (Medicine, Toxicology, Chemistry, Imaging). 

The candidate must fulfill complementary training through the PhD Doctoral Training programmes at the MTCI doctoral school (https://ed563.u-paris.fr/formation-doctorale/) and at the Institut Pasteur (https://www.pasteur.fr/en/myphdpasteur)

Supervisor Nathalie Sauvonnet: https://research.pasteur.fr/en/team/group-nathalie-sauvonnet/ 

Hosting institution Pasteur Institute (France) https://www.pasteur.fr/en/myphdpasteur

Technical information:

• Position location: Paris, France.

• Application deadline: January 6th, 2026

• Interviews: February 9th and 13th, 2026 (be available both days)

• Project start date: September 1st, 2026

• Duration: 3 years

How to Apply

Find the eligibility and application requirements below.

Eligibility Criteria

• Applicants must not have been awarded a doctorate previously.
• Applicants must not have resided or carried out their main activity in the country of the recruiting institution for more than 12 months in the 3 years immediately prior to the date of recruitment. See: https://marie-sklodowska-curie-actions.ec.europa.eu/actions/doctoral-networks ‘What does the funding cover’
• Candidates must have a high level of English proficiency (demonstrated eg by TOEFL, IELTS certification) or by having been educated in an English-speaking country to age 18.
• Candidates must meet all eligibility criteria as outlined in the individual research project descriptions.
• Candidates must meet the entry requirements of the institution to which they apply.

Application Requirements
The candidates will be selected based on the quality of the application, expertise, work experience, and qualifications. In the first instance, an expression of interest should be lodged containing the following documents (in English) consolidated into one single PDF file. As mentioned above, it will increase your chances if you apply to more than one project.

• A current cv (resumé) (max 2 pages).
• A short cover letter, no more than 600 words, that covers the following:
  1: your motivation and key research experience/achievements that demonstrate independent thinking and your ability to complete a PhD. Evidence the skills you claim with the documents you give us.
  2: the original working title of your MSc or BSc thesis.
  3: The first scientific memory that you have (max 250 words)
• A clear statement if and how and what AI tools you used. We recommend you do not use them.
• The table of contents of your thesis
• A research outline (max 500 words) related to the DC topic in which you suggest how you can meet and develop further the research project described in the project advertisement. Be specific: where in your attached certificates can we find proof of the necessary qualifications for the given position?

The following items will be submitted in separately in the application form.

• We suggest you apply for up to 3 PhD positions in StraDiVarious. If you do, list two other choices in order of preference. (You do not need to provide further information.)
• Details of 2 referees (names, contact details) who can provide additional information about your qualifications.
• Official Academic Record - Bachelor's and Master’s Certificates and Transcripts.
• We expect that, since a Master’s Degree is required, you will either have completed it at the time of application, or will do so with the requisite grades and be able to provide a degree certificate by July 1st, 2026. In such a case, acceptance is conditional.
• Demonstration of English-language proficiency (official certificates from language tests, or based on your schooling and where you grew up).
• If we suspect unreported use of AI-generated text, we reserve the right to check using AI-text detection tools and summarily reject the application. This is consistent with our no-tolerance policy towards plagiarism.