02/06/2020
The Human Resources Strategy for Researchers

PhD contract in the field of human gut microbiota, Bioinformatics with an interest in artificial intelligence financed during 3 years by the University Clermont Auvergne

This job offer has expired


  • ORGANISATION/COMPANY
    Université Clermont Auvergne
  • RESEARCH FIELD
    Biological sciences
    Computer science
  • RESEARCHER PROFILE
    First Stage Researcher (R1)
  • APPLICATION DEADLINE
    28/06/2020 00:00 - Europe/Brussels
  • LOCATION
    France › CLERMONT-FERRAND
  • TYPE OF CONTRACT
    Temporary
  • JOB STATUS
    Full-time
  • HOURS PER WEEK
    35 H
  • OFFER STARTING DATE
    01/10/2020
  • REFERENCE NUMBER
    UCA/ANR/001
  • IS THE JOB RELATED TO STAFF POSITION WITHIN A RESEARCH INFRASTRUCTURE?
    Yes

OFFER DESCRIPTION

Subject: From intestinal microbiota to personalized medicine through the

development of new generation neural networks

Supervisor: Pr. Pierre PEYRET

Laboratory: MEDiS (https://www6.ara.inrae.fr/medis/UMR-MEDiS)

Email and phone: pierre.peyret@uca.fr; 33(4)73.17.83.08

Co-advisor(s):

Abstract (up to 10 lines):

The thesis will focus on the development of new deep neural network

approaches enabling the integration of massive heterogeneous data,

including data from the human gut microbiota, to predict evolution of

pathologies in a vision of personalized medicine. These developments in

artificial intelligence will also make it possible to predict the success of

therapeutic treatments and to adapt them. The human gut microbiota,

particularly complex with 100,000 billion bacteria, is involved directly or

indirectly in many digestive and extra-digestive pathologies.

Skills:

Training in Bioinformatics with an interest in artificial intelligence and

studies of the human gut microbiota.

Keywords: New generation neural networks – Microbiota – Health –

Personalized medicine – Integration of heterogeneous data

Description (up to 1 page):

The discovery in recent years of the complexity of the human gut

microbiota (100,000 billion microorganisms) has led to a real revolution in

the field of health. This microbial community plays many roles contributing

to the well-being and good health of the host. It has thus been suggested that

the gut microbiota is directly or indirectly involved in many digestive or

extra-digestive pathologies. Advances in high-throughput sequencing have

made it possible to establish associations between the structures and

functions of the gut microbiota and various diseases. However, the

processing resolutions for big data do not currently allow the precise

identification of microorganisms and functions related to the various

pathologies. The objective of the thesis is to develop new generation deep

neural network approaches allowing the integration of massive

heterogeneous data, including microbiota data, in the context of predictions

and evolution of pathologies in a vision of precision or personalized

medicine. These developments in artificial intelligence will also make it

possible to predict the success of therapeutic treatments and to adapt them.

In fact, human gut microbiota appears very similar from one individual to

another, but finer individual variations lead to changes in microbial

community (dysbiosis) linked to pathologies. In the same way, the response

to therapeutic treatments can be completely different from one individual to

another with in a large number of cases a major role in the composition and

functions of the gut microbiota.

Références (up to ½ page):

Batut, B., Gravouil, K., Defois, C., Hiltemann, S., Brugère, J.B.,

Peyretaillade, E., Peyret, P. (2018). ASaiM: a Galaxy-based framework to

analyze raw shotgun data from microbiota. GigaScience, Jun 1;7(6).

Defois C, Ratel J, Garrait G, Denis S, Le Goff O, Talvas J, Mosoni P,

Engel E, Peyret P. (2018) Food Chemicals Disrupt Human Gut Microbiota

Activity And Impact Intestinal Homeostasis As Revealed By In Vitro Systems.

Sci Rep. Jul 20;8(1):11006.

Gasc, C. and Peyret, P. (2018) Hybridization capture reveals microbial

diversity missed using current profiling methods. Microbiome, Mar

27;6(1):61.

How to candidate?

Contact the supervisor

Pr. Pierre PEYRET

Pierre.peyret@uca.fr

 

 

 

 

 

 
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Benefits

 

 
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Eligibility criteria

 
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Offer Requirements

  • REQUIRED EDUCATION LEVEL
    Other: Master Degree or equivalent

Skills/Qualifications

 

 
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Work location(s)
1 position(s) available at
Microbiology, Digestive Environment, Health (MEDIS)
France
Région Auvergne Rhône-Alpes
CLERMONT-FERRAND
63001
CBRV TSA 50400 28, Place Henri Dunant

Open, Transparent, Merit based Recruitment procedures of Researchers (OTM-R)

Know more about it at Université Clermont Auvergne

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EURAXESS offer ID: 528399

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