Better Nitrogen efficiency by improving Cow Resilience, Eating Dynamics, Breeding and Lifetime Ef...
Fuld tid
Aarhus University (AU)
Applicants are invited for a PhD fellowship/scholarship at Graduate School of Technical Sciences, Aarhus University, Denmark, within the Quantitative Genetics and Genomics programme. The position is available from 1 March 2027 or later. You can submit your application via the link under 'how to apply'.
TitleBetter Nitrogen efficiency by improving Cow Resilience, Eating Dynamics, Breeding and Lifetime Efficiency Research area and project description
The Center for Quantitative Genetics and Genomics (QGG) holds a leading position in cattle breeding research, particularly in genetic studies on data generated by advanced phenotyping technologies such as the CFIT 3D camera system through industry collaboration with VikingGenetics. This state-of-the-art system enables large-scale, non-invasive measurement of feed intake, body weight, and milk production data in over 30,000 cows directly in their production environment. This PhD project will leverage this extensive phenotypic dataset generated by CFIT, in combination with feeding parameters and other phenotypes from the Danish Cattle Database, to develop genetic tools aimed at enhancing nitrogen efficiency, resilience, eating dynamics and feed efficiency. The goal is to develop novel genomic breeding values for nitrogen efficiency, while considering other important breeding goal traits (e.g., productivity, health, fertility) and other traits, such as resilience, eating dynamics and feed efficiency. The project will apply advanced statistical methods, artificial intelligence, and cutting-edge genetic models to support and enhance management and breeding decision-making by dairy farmers. This project offers a unique opportunity to contribute to the green transition in agriculture by breeding cows that are both more sustainable and economically viable for the future of Danish dairy farming. We encourage candidates finishing their MSc in summer 2027 also to apply. Qualifications and specific competences
A relevant master’s degree (120 ECTS) in Animal Breeding
Experience with data handling softwares (e.g., R, SAS, Python, Unix Shell) and genetic softwares (e.g., DMU, BLUPF90, AIREML).
Background in working with Livestock data is an advantage.
Can speak and write English fluently is a prerequisite. Place of employment and place of work
The place of employment is Aarhus University, and the place of work is Center for Quantitative Genetics and Genomics, C.F. Møllers Allé 3, 8000 Aarhus C., Denmark. Contacts
Applicants seeking further information regarding the PhD position are invited to contact:
- Associate Professor Bingjie Li, e-mail: Se e-mailadresse på nature.com (main supervisor)
- Tenure Track Assistant Professor Rasmus Bak Stephansen, e-mail: Se e-mailadresse på nature.com (co-supervisor)
Please follow this link to submit your application. Application deadline is 29 November 2026 23:59 CET. Preferred starting date is 01 March 2027. For technical reasons, you must upload a project description. Please copy the project description above and upload it as a PDF in the application. Please note:
- Only documents received prior to the application deadline will be evaluated. Thus, documents sent after deadline will not be considered.
- The programme committee may request further information or invite the applicant to attend an interview.
- Shortlisting will be used, which means that the evaluation committee only will evaluate the most relevant applications.
Salary and terms as agreed between the Danish Ministry of Taxation and the Confederation of Professional Unions. You will be employed as an academic staff member at basic salary grades 4–8. As a PhD fellow you will also receive a monthly non-pensionable allowance. Aarhus University’s ambition is to be an attractive and inspiring workplace for all and to foster a culture in which each individual has opportunities to thrive, achieve and develop. We view equality and diversity as assets, and we welcome all applicants. The application must be submitted via the online recruitment system, which can be accessed under ‘How to apply’.
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