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Bingjie Li

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3 days ago

PhD in Better Nitrogen efficiency by improving Cow Resilience, Eating Dynamics, Breeding and Lifetime Efficiency Aarhus University in Denmark

Degree Level

PhD

Field of study

Computer Science

Funding

Available

Deadline

Nov 29, 2026

Country flag

Country

Denmark

University

Aarhus University

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Keywords

Computer Science
Environmental Science
Agriculture
Biology
Artificial Intelligence
Animal Breeding
Phenotyping
Quantitative Genetics
Feed Efficiency
Resiliency
Genomic
Statistics
Cattle

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About this position

PhD opportunity at Aarhus University, Denmark in the Graduate School of Technical Sciences, within the Quantitative Genetics and Genomics programme.

This project is hosted by the Center for Quantitative Genetics and Genomics (QGG), a leading research environment in cattle breeding and quantitative genetics. The PhD will use large-scale phenotypic data from advanced technologies such as the CFIT 3D camera system, developed in collaboration with VikingGenetics, together with feeding parameters and other records from the Danish Cattle Database. The goal is to develop genetic tools and novel genomic breeding values that improve nitrogen efficiency, resilience, eating dynamics, and feed efficiency in dairy cows, while also accounting for productivity, health, fertility, and lifetime efficiency.

The research combines advanced statistical methods, artificial intelligence, and cutting-edge genetic models to support breeding and management decisions for dairy farmers. The project is framed by the green transition in agriculture and aims to contribute to more sustainable and economically viable dairy production in Denmark. This is a strong fit for applicants interested in animal breeding, dairy genetics, livestock phenotyping, and data-driven agricultural research.

Eligibility highlights: a relevant master’s degree in Animal Breeding (120 ECTS) is required; experience with R, SAS, Python, Unix Shell, and genetic software such as DMU, BLUPF90, and AIREML is advantageous; experience with livestock data is a plus; fluent English is required. Applicants finishing their MSc in summer 2027 are also encouraged to apply.

Funding and timing: the post is described as a PhD Fellowship/Scholarship, but specific funding details are not stated. The position is available from 1 March 2027 or later, and the application deadline is 29 November 2026 at 23:59 CET.

Application notes: applicants should apply through the online portal, upload the required project description as a PDF, and ensure all documents are submitted before the deadline. Shortlisting may be used and the committee may request additional information or an interview.

Funding details

Available

What's required

A relevant master's degree (120 ECTS) in Animal Breeding is required. Experience with data handling software such as R, SAS, Python, and Unix Shell, and with genetic software such as DMU, BLUPF90, and AIREML, is expected. Background working with livestock data is an advantage. Fluent spoken and written English is a prerequisite. Candidates finishing their MSc in summer 2027 are encouraged to apply.

How to apply

Apply through the online application link and click the 'Apply' button. Upload a project description as a PDF using the text provided in the post. Submit all required documents before the deadline; late documents will not be considered.

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Professors

Associate Professor at Aarhus University

University Name
Country flag

Denmark

Research Interests

Statistics

Artificial Intelligence

Genomic

Agriculture

Biology

Tenure Track Assistant Professor at Aarhus University

University Name
Country flag

Denmark

Research Interests

Artificial Intelligence

Statistics

Resiliency

Biology

Agriculture