PhD Position in Quantitative Genetics, Genomics, and Risk-Aware Selection in Cattle at Aarhus University

Aarhus University is offering a PhD position in the field of Quantitative Genetics and Genomics, focusing on the development of a novel framework for risk-aware selection in cattle for long-term sustainability. The project aims to create advanced methods that enable the cattle sector to select breeding bulls supporting both economic and sustainable development in dairy and beef production. The research will address the challenge of uncertain future production conditions by developing risk management tools that optimize genetic progress, economic returns, and sustainability. The project is expected to significantly reduce greenhouse gas emissions and improve feed efficiency, contributing to reductions in nitrogen and phosphorus emissions. The commercial partner anticipates economic gains through increased market share in the export of bull semen. The research team will include geneticists, breeding specialists, economists, and data analysts, working collaboratively to implement the developed tools in cattle breeding processes. Applicants should hold a master's degree in Animal Science, Quantitative Genetics, Economics, or a related field, and possess strong programming skills (preferably in R or Python). Excellent English communication skills and the ability to work in interdisciplinary and international teams are required. The position is based at the Center for Quantitative Genetics and Genomics, Aarhus University, Denmark. The application deadline is 15 April 2026, with a preferred start date of 1 August 2026. Salary and employment terms follow the applicable collective agreement. For more information, applicants may contact the main supervisor, Hanne Marie Nielsen, or the co-supervisor, Alban Etienne René Bouquet. Applications must be submitted online, including a PDF of the project description and all required documents. Keywords: Quantitative Genetics, Genomics, Animal Science, Risk Management, Cattle Breeding, Sustainability, Dairy Production, Beef Production, Programming, Economics.