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- Ph.D. scholarship - Adaptive physiology of growing beef cattle
Description
This is how you can contribute
- Planning and active participation to a beef cattle experiment
- Coordination of sampling and measurements on cattle, both alive and at the slaughterhouse, using state-of-the-art imaging technologies
- Management of longitudinal datasets, advance statistical analyses and interpretation
- Optimization and evaluation of a mechanistic model of the growth function and the kinetics of the body fat-to-lean ratio
- Communication and publication of results in scientific journals, scientific reporting for funders and stakeholders
- Project management and collaboration within an international consortium
In a nutshell
The PhD candidate will contribute to the research project “iREACT – IntegRativE biology approach to understand Adaptive physiology of bovine reared on grass to produce low Carbon meaT”. Grass-fed cattle production should be considered in the context of a circular economy, as well as for local and global food security but remains a challenging task for farmers. Grass availability remains seasonal, uncertain, and sensitive to climate changes, resulting in disrupted cattle production itineraries and the discontinuous availability of nutrients. For beef cattle, this means that maintaining a satisfactory level of growth performance without compromising animal health and welfare or meat quality is a priority.
The rationale of the iREACT project is that beef-on-dairy crossbred cattle combine high efficiency and resilience capabilities due to adequate balance between fat tissue relative to muscle depositions (fat-to-lean ratio) and consequently mobilise body energy reserves when faced with periods of reduced feed availability. The PhD candidate will focus on the development of imaging techniques and mechanistic model for monitoring and predicting the fat-to-lean ratio during heifers' growth.
You have a background in animal science, nutrition, physiology, bioinformatics or a related field, with a strong interest in applied research and new technologies in agriculture. You are interested in precision livestock farming, beef meat production system and in adaptative physiology of cattle. You are interested in combining animal experimentation with computational methods. You have good computer skills and some experience in handling data and models, as well as scientific writing skills, along with motivation to further develop these skills.
iREACT is a SNF and ANR funded project, conducted within a strong research network involving Agroscope and French institutions (INRAE UMRH and UMR PEGASE, Inria and IMT). The PhD candidate will additionally benefit of academic supervision at University of Fribourg offering an interdisciplinary and applied research environment at the interface of animal nutrition and data sciences.
Additional information
The 'Ruminant Nutrition and Emissions' Research Group is represented at the Posieux and Tänikon sites. We deal with ruminant physiology, nutrition and husbandry in roughage-focused feeding systems with the aim of sustainably improving nutrient efficiency, lowering emissions from cattle husbandry, reducing nutrient-related production diseases, and maintaining high product quality.
If this challenge appeals to you, we look forward to receiving your online application at https://jobs.admin.ch, ref. no. JRQ$540-19036. (English is not an official Swiss language, please choose German, French or Italian as correspondence language).
For further information please contact Mr. Sylvain Lerch, Research Associate, Tel. +41 58 461 41 29.
Start date: 1 September. 2026. The post is for a fixed term until 31.08.2030.
Requirements
This makes you unique
- Master or equivalent degree in animal sciences, biology, bioinformatics or a related field
- Strong interest in adaptive biology, ruminant physiology, new technologies and precision livestock farming for sustainable beef production
- Experience in statistics and scientific writing. Very good IT skills. Additional experience in animal experimentation, modeling or knowledge of programming or algorithms would be a plus
- Ability to work independently and collaborate within a multidisciplinary and international research consortium
- Excellent organizational and communication skills
- Knowledge of two official Swiss languages and English

