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Develop prediction models to manage trade-offs and optimise resilience and efficiency in small ruminants

  • Application Deadline
    Deadline:
    15 September 2020
    (application date has expired)
  • Job Salary
    £2,000 to £2,200 euros (net salary)
  • Website
  • Contact Name
    Contact:
    Dr PUILLET Laurence


The French National Research Institute for Agriculture, Food, and the Environment (INRAE) is a public research establishment. It is a community of 12,000 people with more than 200 research units and 42 experimental units located throughout France. The institute is among the world leaders in agricultural and food sciences, in plant and animal sciences, and is 11th in the world in ecology and environment. INRAE’s main goal is to be a key player in the transitions necessary to address major global challenges. In the face of the increase in population, climate change, scarcity of resources and decline in biodiversity, the institute develops solutions for multiperformance agriculture, high quality food and sustainable management of resources and ecosystems.

WORK ENVIRONMENT, MISSIONS AND ACTIVITIES
 The postdoctoral fellow will join an interdisciplinary European project (funded by the Research and Innovation H2020 program) called SMARTER (Small Ruminant Breeding for Efficiency and Resilience, https://www.smarterproject.eu/). This project aims at improving resilience and efficiency (R&E) of the sheep and goat sectors at the animal, population/breed and farming system levels. The overall goal is i) to phenotypically and genetically characterize and understand novel R&E related traits, ii) to improve and develop new genomic prediction techniques, and iii) to establish new breeding and management strategies that include those novel R&E related traits according to their importance and relevance to various systems, breeds and environments. The postdoctoral project will contribute to a better understand and ability to predict trade-offs and synergies between R&E traits, depending on challenging environmental conditions. An existing prediction model at animal level, based on energy acquisition and allocation throughout lifetime, will be used to allow trade-offs to be explicitly represented. A database will be developed from unique experimental studies on divergent genetic lines of dairy goats for longevity. It will provide knowledge on how challenging conditions may impact the animal’s life trajectory, both in the short and the long term. This knowledge will be combined with the existing life trajectory model to explore “what if” questions at herd/population level and evaluate how management and breeding strategies affect R&E traits, across different environments.
 The main mission of the postdoc will be to i) extend an existing mechanistic model of the dairy cow to dairy goat and calibrate for divergent genetic lines; ii) integrate knowledge from experiments on short term nutritional challenges to refine resilience component of the model; iii) design and run simulations at herd level to evaluate R&E traits in various farming systems; iv) propose an adaptation of the model to include infectious challenges.
 The research will be carried out at the MoSAR lab in Paris and Palaiseau. The postdoc fellow will work with Laurence Puillet and Nicolas Friggens and collaborate with Frederic Douhard from GenPhyse lab (INRAE Toulouse) and Andrea Doeschl-Wilson from Roslin Insitute (University of Edinburgh).

TRAINING AND SKILLS

 PhD in biology/agricultural sciences or applied math/stats
 Excellent communication skills to interact in an interdisciplinary environment (geneticists, animal and farming systems scientists, modellers)
 Expertise in modelling dynamic systems (ODE, parameter estimation, sensitivity analysis) and dedicated software: R, Python
 Good knowledge and/or strong motivation in biological systems


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