Know more

Our use of cookies

Cookies are a set of data stored on a user’s device when the user browses a web site. The data is in a file containing an ID number, the name of the server which deposited it and, in some cases, an expiry date. We use cookies to record information about your visit, language of preference, and other parameters on the site in order to optimise your next visit and make the site even more useful to you.

To improve your experience, we use cookies to store certain browsing information and provide secure navigation, and to collect statistics with a view to improve the site’s features. For a complete list of the cookies we use, download “Ghostery”, a free plug-in for browsers which can detect, and, in some cases, block cookies.

Ghostery is available here for free: https://www.ghostery.com/fr/products/

You can also visit the CNIL web site for instructions on how to configure your browser to manage cookie storage on your device.

In the case of third-party advertising cookies, you can also visit the following site: http://www.youronlinechoices.com/fr/controler-ses-cookies/, offered by digital advertising professionals within the European Digital Advertising Alliance (EDAA). From the site, you can deny or accept the cookies used by advertising professionals who are members.

It is also possible to block certain third-party cookies directly via publishers:

Cookie type

Means of blocking

Analytical and performance cookies

Realytics
Google Analytics
Spoteffects
Optimizely

Targeted advertising cookies

DoubleClick
Mediarithmics

The following types of cookies may be used on our websites:

Mandatory cookies

Functional cookies

Social media and advertising cookies

These cookies are needed to ensure the proper functioning of the site and cannot be disabled. They help ensure a secure connection and the basic availability of our website.

These cookies allow us to analyse site use in order to measure and optimise performance. They allow us to store your sign-in information and display the different components of our website in a more coherent way.

These cookies are used by advertising agencies such as Google and by social media sites such as LinkedIn and Facebook. Among other things, they allow pages to be shared on social media, the posting of comments, and the publication (on our site or elsewhere) of ads that reflect your centres of interest.

Our EZPublish content management system (CMS) uses CAS and PHP session cookies and the New Relic cookie for monitoring purposes (IP, response times).

These cookies are deleted at the end of the browsing session (when you log off or close your browser window)

Our EZPublish content management system (CMS) uses the XiTi cookie to measure traffic. Our service provider is AT Internet. This company stores data (IPs, date and time of access, length of the visit and pages viewed) for six months.

Our EZPublish content management system (CMS) does not use this type of cookie.

For more information about the cookies we use, contact INRA’s Data Protection Officer by email at cil-dpo@inra.fr or by post at:

INRA
24, chemin de Borde Rouge –Auzeville – CS52627
31326 Castanet Tolosan CEDEX - France

Dernière mise à jour : Mai 2018

Menu Logo Principal logo Université Clermont Auvergne & associés

Human Nutrition Unit

Zone de texte éditable et éditée et rééditée

Positions Training Thesis PostDoc

.

Post Doc Position   January 2021

Contact:

Dr. Sergio Polakof

33 (0)4 73 62 48 95   

WEB

       

sergio.polakof@inrae.fr

Scientific project:

Frailty is characterized by the loss of physiological homeostasis and capability to handle modifications of its environment. It is partly driven by mobility capacities and nutritional features. To minimize risks, optimize outcomes and maintain independency for aged patients, it is important to identify the level of frailty rapidly and accurately even in non-geriatric services. Here, in a German cohort of elderly patients, we aim at obtaining a metabolomics-based signature able to identify at discharge, those metabotypes potentially responsive to future (at home) nutritional and/or physical activity interventions. This tool would provide a more accurate and fast diagnosis, improving the identification of the patient needs and enabling a more personalised care pathway during the hospital stay and after discharge.

Key Words: 

Elderly, Metabolomics biomarkers, Nutritional status, Mobility, Frailty

Location:

The fellow will be recruited by the Université Clermont Auvergne/INRAE (France) but will be required to carry out  first his/her research work at the Charité University Hospital in Berlin under the supervision of Pr. K. Norman ( PhD,Charité Berlin and DIfE Postdam) and  then, at the INRAE Research Centre in France. In Germany, a clustering of the geriatric patients of the Wonder cohort (n=500) will be made and in France, the metabolomics analyses will be carried out with the management, interpretation and modeling of the big data generated.

Salary:  

2 100€ - 2 450€ net of charge per month depending of the years of expertise after the PhD

Duration:

18 months

Expertise/Background requested:

The candidate must have training and skills focused on biology with a particular interest in metabolism, metabolomics and epidemiology. Knowledge of statistics (univariate, multivariate, clustering, predictive models) and metabolomics data analysis and treatment are also requested. The training of various skills (biochemistry, nutrition) within a transdisciplinary project supervised by several specialists should be a central motivation of the candidate. Fluency in English is required.