Postdoctoral position: developping biomarker-assisted predictions of animal feed efficiency and its determinants in cattle
Deadline for applications
Date of publication


Details on the type of contract
Postdoctoral contract
Duration of contract
22 months + possible extension of 12 months

from 2 426 to 2 643 euros/month (gross salary) according to experience
Professional field
Informatics, statistics and scientific calculations


Name of unit of assignment
UMR1213 UMRH Unité Mixte de Recherche sur les Herbivores
Address of unit of assignment
Region of assignment
Auvergne Rhône-Alpes


Working environment

Research unit:

UMR1213 Herbivores is a joint research unit associating Inra and VetAgro Sup. It contributes to the design of sustainable farming systems for herbivores that seek to reconcile production efficiency, product quality and socio-economic viability with environmental protection and valuation, and animal welfare. UMR1213 Herbivores assesses both on-farm practices and predominant and alternative systems of herbivore farming, and proposes innovative techniques with high environmental value. To achieve this aim, UMR1213 Herbivores analyses and integrates the underlying biological mechanisms, and establishes laws for animal responses with approaches ranging from high-throughput techniques to modelling and decision support tools for various stakeholders (producers, consumers, citizens, and policy-makers).


The Unit is divided into 5 research teams including DINAMIC team (Digestion, Nutrients, Feed and Microbiota). DINAMIC team’s focus on the study of mechanisms underlying ingestion, rumen fermentation, digestion and metabolism allowing to monitor nutrition of ruminants considering several dimensions: efficiency of feed utilization, environmental services/disservices (including limitation of metane (CH4) and nitrogen (N) wastes), but also digestive comfort, and quality of products. DINAMIC team’s research contributes to the conception of ruminants feeding systems based on human inedible resources by addressing the following topics: i) characterization of ruminant feeds and diets and development of prediction methods, ii) quantification of intake, digestive and metabolic fluxes of nutrients to understand and predict the responses of digestion and metabolism to variations of intake and diet composition, and to develop indicators of digestive and metabolic functions and iii) characterization of the digestive microbial ecosystem and its interaction with the diet and host to understand and control the metabolism of the holobiont (i.e. microbiota and host as an entity).



Ruminant production is of considerable economic and societal value. Ruminants can transform human-inedible feed (e.g. grasses and forages rich in cellulose) into high-quality human-edible food (e.g. meat, milk). However, this conversion has a low efficiency, especially in ruminants fed high-forage diets, and is associated with N pollution and greenhouse gas emissions (GHG). Given the growing human population, the scarcity of natural resources and the need to preserve our environment, improving the conversion of feed resources into animal products (i.e. animal feed efficiency) is becoming a major challenge for ruminant productions (Makkar and Beever, 2013). The need to improve animal feed efficiency at the same time as reducing anthropogenic GHG emissions and N pollution has been highlighted by the EU (H2020, FACCE JPI, AnimalChange FP7 project, SusAn ERA-NET, GAS ERA-NET, Standing Committee on Agricultural Research-SCAR, EFSA), the Animal Task Force-ATF (European public private partnership), the FAO, the Global Research Alliance on Greenhouse Gases (GRA GHG), and by the recent outcomes from the COP 21 meeting in Paris.


The biological determinants of animal feed efficiency, and particularly at the level of animal-to-animal variation, are still far from being fully understood. However, these determinants need to be comprehended if we want to improve animal feed efficiency through genetic selection and novel nutritional strategies. Gold standard methods to measure determinants of animal feed efficiency, such as the confinement in stalls for total collection of faeces and urine or in chambers for CH4 emissions, are most of the time intrusive, expensive and time-consuming. Preliminary work (Dehareng et al., 2012; Cantalapiedra-Hijar et al., 2015; Decruyenaere et al., 2015) have identified biomarkers that are easier to implement, less invasive for animals and less costly. Moreover, although biomarkers might be less accurate than the gold standard methods, they can be measured frequently to reduce random noise. However, their applicability at a large scale particularly for individual phenotyping, remains to be evaluated.


Within the Smartcow EU-H2020 project (an integrated infrastructure for increased research capability and innovation in the European cattle sector; Coordinator: R. Baumont [2018-2020]) we aim to focus on the most promising biomarkers to predict total-tract diet digestibility, N balance and animal overall feed efficiency both in dairy and beef cattle and assessing their range of applicability across diets and individuals. This work will be based on existing and new samples obtained within the project and will provide new measurement opportunities and less invasive approaches for the participating infrastructures and future EU projects. At INRA center of Theix, the role of the post-doctoral fellow will be to participate in the WP6 (Work-package leader: C. Martin; Task leader: G. Cantalapiedra-Hijar) through i) the creation of a large EU database including existing gold-standard measurements for digestibility, N balance and feed efficiecy in cattle together with identified biomarkers analyzed in different biological matrices (Month 1- Month 10), ii) the statiscial anylisis of this database by mixed-effect modelling to develop biomarker-assisted predictions of the targeted gold-standard measurments and for identying the limits and range of validity of the different biomarkers (Month 10 – Month 14 & Month 16 – Month 22), iii) establishing a sampling protocol according to preliminary results before the onset of new experiments to be conducted by the different EU partners within the project (Month 14 – Month 16), iv) cross-validate the obtained prediction equations from external measurements and samples (Month 22 – Month 26) and v) publish predictions equations in international peer-review papers (Month 26 – Month 34). The post-doctoral fellow must interact with EU-partners participating to the project and conduct a short-training period of 3-6 months in Scottland (SRUC; R. Dewhurst).

Training and skills required


Candidate skills : phD in animal nutrition, modelling, mixed-model statistical analysis, database management, English (read, written, spoken), exchange qualities.



Send a motivation letter and a CV to : Gonzalo CANTALAPIEDRA-HIJAR / Cécile MARTIN




(33) 04 73 62 41 06 / (33) 04 73 62 40 55