PhD Scholarship: Genetic Improvement of Dairy Cow Longevity, Using Large-Scale Body Weight Data from an AI-Camera System

Genetic Improvement of Dairy Cow Longevity, Using Large-Scale Body Weight Data from an AI-Camera System (Long Live the Dairy Cow)

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 01 January 2026 or later. You can submit your application via the link under 'how to apply'.

Title

Genetic Improvement of Dairy Cow Longevity, Using Large-Scale Body Weight Data from an AI-Camera System (Long Live the Dairy Cow)

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 CowFIT 3D camera system through industry collaboration with VikingGenetics. This state-of-the-art system enables large-scale, non-invasive measurement of body weight in over 30,000 cows directly in their production environment.

This PhD project will leverage the extensive phenotypic data generated by CowFIT, in combination with other phenotypes from the Danish Cattle Database, to develop both management and genetic tools aimed at extending the productive lifespan and efficiency of dairy cows. The goal is to enhance the economic sustainability of Danish dairy farming while simultaneously reducing the carbon footprint of milk production.

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 includes tools for dairy cattle management traits such as calving weight, energy balance, and maturity, as well as genetic tools targeting heifer growth, carcass development, and energy efficiency, all with the aim of improving the productive lifespan of dairy cows. Additionally, the project aim to enhance the genomic accuracy on existing breeding goal traits (e.g., longevity, functional traits, Saved Feed) by including indicator information from the developed traits, and validating with Interbull methods.

• Project description. For technical reasons, you must upload a project description. Please simply copy the project description above and upload it as a PDF in the application. 

Qualifications and specific competences

Applicants to the PhD position must have a relevant Master’s degree (120 ECTS), with experience in Animal Breeding.

Experience with data handling softwares (e.g., R, SAS, Python, Unix Shell) and genetic softwares (e.g., DMU, F90, 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 C.F. Møllers Allé 3, Bldg. 1130, 8000 Aarhus C. The area of employment is Aarhus University with related departments.

Contacts

Applicants seeking further information regarding the PhD position are invited to contact: 

• Associate Professor Emre Karaman, emre@qgg.au.dk (main supervisor)
• PostDoc Rasmus Bak Stephansen, rasmus.stephansen@qgg.au.dk (co-supervisor) 

For information about application requirements and mandatory attachments, please see our application guide. If answers cannot be found there, please contact: 

• admission.gradschool.tech@au.dk 

How to apply:

Please submit your application online by clicking the Apply button above.

Application deadline is 30 September 2025 at 23:59 CEST.

Preferred starting date is 1 January 2026.

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