Applicants are invited for a PhD fellowship/scholarship at Graduate School of Technical Sciences, Aarhus University, Denmark, within the Animal and Veterinary Sciences programme. The position is available from 1 October 2024 or later. This MOVEC project is related to bioinformatics and systems biology analyses of data from cattle Artificial Reproductive Technologies (ART) with practical implications for modern Dairy herd management. The successful applicant will become part of the newly established teaching and research group/areas around Multiomics, Systems Biology and Bioinformatics at the Institute for Animal & Veterinary Sciences (ANIVET) under the leadership of Prof. Haja Kadarmideen (HK). Project leverages the availability of NGS based epigenomic & transcriptomic profiles of in vivo and in vitro produced embryos and calves from externally funded research projects, along with relevant parameters and phenotypic data.
Main objectives in this PhD project are to i) conduct Multiomics Systems biology and Bioinformatics (MSB) analyses on embryo’s and calf’s epigenomics (WGBS) and transcriptomics (RNASeq) datasets, ii) conduct MSB analyses on embryos derived from bulls with vastly different sperm epigenomic profiles and associate with embryo development and embryo quality and to iii) to evaluate the impact of these omics technologies, ART data as well as new phenotypes in future of dairy cattle management. The project will have resources for data analytics (licensed and open software, powerful PC / hardware, High Performance Computing infrastructure etc.) and for more targeted validation of epigenomic and transcriptomic biomarkers.
The applicant will acquire and apply genomic, epigenomic, systems biology and statistical-bioinformatics expertise for detection of key genes/molecular pathways, for the development of biomarkers and for statistical predictions of ART outcomes, given the multiomics profiles. The student will also be trained to work with simulation programs to assess the impact of new phenotypic, ART and multiomics technologies at the animal level and farm level management.
In addition to main supervisor (HK), two co-supervisors with complimentary disciplinary expertise will be a part of the project team at AU. An assistant professor with expertise in phenotyping and management of Dairy herds and a full professor with expertise in ART (MOET, IVF) and reproductive biology. The successful candidate will have close collaborations with experts in the project areas located in INRAE (France), Utrecht University (Netherlands) and University of Copenhagen (Denmark).
Applicants to this PhD position must hold a Masters’ degree (120 ECTS) in directly relevant field (Genomics or Bioinformatics or Systems biology or MultiOmics data science) preferably within Animal & Veterinary sciences. The ideal candidate should have expertise or experience with NGS-based omics (genomics or epigenomics and transcriptomics) data types and phenotype data using standard software tools in R and Python in Windows/UNIX. It is expected that the successful candidate will publish research findings in peer-reviewed international journals and has strong motivation to translate findings into practical applications in Dairy herd management, reproduction, and genetic improvement.
The successful applicant will initially develop a more comprehensive research/PhD plan together with the supervisors of the project, particularly the main supervisor Prof. Haja Kadarmideen.
Further requirements include fluency in English, excellent writing and verbal communication skills, independence, teamwork, and the willingness to contribute to the teaching, to the guidance of Bachelor/Master projects and to the day-to-day work within Genomics/Multiomics, Systems Biology and Bioinformatics at ANIVET.
SUBMIT applications ONLINE via this university link:
phd.tech.au.dk/for-applicants/apply-here/saeropslag/phd-in-systems-biology-bioinformatics-multiomic-systems-biology-of-in-vitro-produced-cattle-embryos-and-calves-movec
PLEASE DO NOT APPLY VIA EMAIL to the supervisor(s). THEY WILL NOT BE CONSIDERED