PhD in Computational Biology and Genomic Prediction in Dairy Cattle at La Trobe University La Trobe University in Australia

La Trobe University, in collaboration with AgriBio and the ARC Training Centre in Predictive Breeding, is offering a fully funded PhD opportunity in computational biology and genomics. The project focuses on modelling genotype by environment by management (GxExM) interactions to improve genomic prediction in dairy cattle. The successful candidate will join a leading computational biology team in Melbourne, Australia, and work on developing mechanistic models to incorporate GxExM into genome-wide analyses and prediction.

The research will involve studying traits such as feed efficiency, animal health, and resilience. The student will use existing phenotype data to fit and calibrate models, linking them with cow genotypes. The overarching hypothesis is that integrating additional GxExM information will enhance the accuracy of genomic prediction in dairy cattle. The project is part of a team with a strong track record in animal quantitative genetics, including contributions to genomic selection, the 1000 Bull Genome project, BayesR, the Sustainability Index, FAETH score, and the Bovine Long-read consortium.

Benefits include a prestigious ARC scholarship of $AUD37,000 per year for up to 4 years, international travel support of $AUD5,000 per year, relocation assistance of approximately $AUD2,000, and access to advanced technologies and professional development. Projects can be tailored to the student's skills and interests, with a focus on method development, programming, or data sciences as appropriate.

Applicants should have a strong background in computational biology, statistics, data science, or related fields. Experience in quantitative genetics, programming, or method development is highly desirable. Interested candidates are encouraged to contact the supervisors for more information and to discuss their suitability for the project.

For inquiries, contact: [email protected], [email protected], or [email protected].