法国国家信息与自动化研究所(INRIA)2022年招聘博士后（抗生素耐药性的快速诊断）

法国国家信息与自动化研究所(INRIA)2022年招聘博士后（抗生素耐药性的快速诊断）

法国国家信息与自动化研究所（或称法国国立计算机及自动化研究院），法文为 Institut national de recherche en informatique et en automatique (简称INRIA)，其重点研究领域为计算机科学，控制理论及应用数学。该研究院于1967年在巴黎附近的罗克库尔的创立，为法国国家科研机构，直属于法国研究部和法国经济财政工业部。INRIA是世界著名的科研机构，其科研实力在世界大学和科研机构的计算机领域中排名前列。

Post-Doctoral Research Visit F/M Rapid diagnostics of antibiotic resistance

Inria

2022-05584 - Post-Doctoral Research Visit F/M Rapid diagnostics of antibiotic resistance

Contract type : Fixed-term contract

Level of qualifications required : PhD or equivalent

Fonction : Post-Doctoral Research Visit

About the research centre or Inria department

The Inria Centre at Rennes University is one of Inria's eight centres and has more than thirty research teams. The Inria Centre is a major and recognized player in the field of digital sciences. It is at the heart of a rich R&D and innovation ecosystem: highly innovative PMEs, large industrial groups, competitiveness clusters, research and higher education players, laboratories of excellence, technological research institute, etc.

Context

The project takes place in the context of the BARD(e) Inria Exploratory Action (https: // www. inria.fr/en/barde), focused on developing better and faster methods for diagnostics of antibiotic resistance.

The postdoctoral researcher will work under the supervision of Dr. Karel Brinda (karel.brinda@inria.fr) within the GENSCALE team at INRIA/IRISA Rennes (https: // team.inria.fr/genscale/). She/he will collaborate extensively with an INRIA software engineer and external clinical partners at CHU/INSERM Rennes.

Assignment

Antibiotic resistance is a major public health threat, and rapid diagnostics are becoming a crucial tool for clinicians to identify effective antibiotics for patients with serious bacterial infections. However, traditional diagnostic approaches are slow because they involve culturing of bacteria. A new generation of sequencers has offered the prospect of obtaining within- hours diagnoses via the analysis of the DNA contained in uncultured patient samples. The goal of this AEx is to explore, in this context, the computational challenges of resistance diagnostics, starting from the recently developed ultra-rapid nearest neighbor identification approach proposed in https: // www. nature.com/articles/s41564-019-0656-6

Main activities :

Developing novel approaches for diagnostics of antibiotic resistance

Analyzing public sequencing data

Sequencing and analyzing clinical samples

Developing genome databases

Writing reports and papers and presenting work at conferences

Additional activities :

Coordination of data and information exchange with experimental and clinical partners.

Collaboration with computer scientists, notably a software engineer associated with the project

Training of interns, PhD students, and engineers

Skills

Technical skills and competence

Completed PhD in a biology-related field

Basic computational competence (Unix, Git, Snakemake, R/Python) or willingness to rapidly acquire it

Advanced experience with microbiology techniques such as PCR, nanopore sequencing, Illumina sequencing, and broth microdilution

Knowledge of mechanisms of antibiotic resistance

Good understanding of processes in clinical microbiology laboratories and the associated reporting standards (eg EUCAST)

Language skills

English (main communication language)

Reasonable French (preferred by clinical partners)

Relational skills

Excellent interpersonal and communication skills

Good oral and written communication skills

Ability to lead projects in an interdisciplinary environment

Additional/optional

Previous experience of working with enterococci

Previous work experience in a clinical microbiology lab

Familiarity with the systems of national collections of bacterial strains

Didactic competence

Benefits package

Subsidized meals

Partial reimbursement of public transport costs

Possibility of teleworking (90 days per year) and flexible organization of working hours

Partial payment of insurance costs

Remuneration

Monthly gross salary amounting to 2 746 euros

General Information

Theme/Domain : Computational Biology

Town/city : Rennes

Inria Center : Centre Inria de l'Université de Rennes

Starting date : 2023-01-01

Duration of contract : 2 years

Deadline to apply : 2022-12-31

Contacts

Inria Team : GENSCALE

Recruiter : Brinda Karel / karel.brinda@inria.fr