Projeto PRR

Sumário

The aim of the Final Conference of the European Science Foundation’s Genomic Resources program, held in 2014 at Cardiff University and which involved scientists and policymakers from South and East Asia, North America, Europe and Africa, was to identify a series of pressing questions for a research and policy agenda for Farm Animal Genetic Resources (FAnGR) conservation for the following decade. The overall conclusion, published in Frontiers and Genetics (https://doi.org/10.3389/fgene.2015.00314), was that the livestock sector needed to make a concerted effort to enable the democratisation of the «omics» tools available, to ensure they are applied in the context of sustainable animal breeding. Almost a decade later, there is still a large gap between the current state-of-the-art in the use of such tools and its application to many non-commercial and local breeds, hampering the consistent utilisation of «big data» as indicators of genetic erosion and diversity. More so, as new technologies (i.e. high-throughput phenotyping and genotyping, (pan)genomics, epigenetics, metagenomics, etc.) are offering potentially relevant new indicators. In the Iberian Peninsula, the biodiversity of domesticated animal species (e.g. cattle, sheep, goats, pigs and dogs) is exceptionally high with a large number of well-adapted native breeds. The identification of genomic markers which are associated with adaptation to ecosystems and disease resistance, together with molecular markers for production traits, can be used for breeding in the future and for the continued sustainable utilisation of these locally adapted farm animal genetic resources. In the framework of the research developed at the Faculty of Veterinary Medicine (FMV), in collaboration with the Centre for Interdisciplinary Research in Animal Health (CIISA) and the Associated Laboratory for Animal and Veterinary Science (AL4AnimalS), the hiring of an Assistant Professor in Computational Biology will be instrumental to develop integrative «big data» studies that link areas of knowledge, from image analysis to statistics and bioinformatics, in the fields of Animal Science and Animal Health. The position holder will be responsible to carry out data analyses and develop bioinformatics pipelines in the context of ongoing and future collaborative projects to:Characterize biodiversity and the processes of breed differentiation, actively contributing to protect local FAnGR.Improve our understanding of the molecular and physiological mechanisms underlying adaptation, immunity, and disease resistance traits in domestic animal species.Studying the impact and resilience of local FAnGR to climate change, effectively fostering innovation in the fields of Animal Science and Animal Health.It is a requirement that the Assistant Professor can demonstrate solid knowledge, skills, and experience in fields of Computational Biology, Bioinformatics and Statistics applied to Animal Science, and the analysis of large genomic datasets relevant to the research represented at the faculty and Associated Laboratory. Proficiency in programming languages, such as Python and R, is needed. Applicants who can demonstrate solid knowledge, skills and experience relevant to the following list of topics will be considered favourably: metagenomics, microbiome analysis, validation of machine learning methods. The ideal applicant will be distinguished by a record of research excellence in these areas, showcased through significant scientific achievements, publications in high-profile scientific journals, consolidated national and international collaborations, securing and managing research grants in cutting-edge research fields, and a demonstrated history of excellence in university teaching and student mentorship. Therefore, it is expected that the candidate: is proficient in both written and oral English; has a proactive attitude; can work independently while being a team player; and can communicate effectively with people with a variety of backgrounds and expertise.The role includes a teaching commitment capped at four hours per week at the faculty, specifically within the Doctoral Program in Veterinary Medicine (Statistics Applied to Biological Sciences), ensuring the cutting-edge research and breakthroughs developed will directly enhance the educational journey of our students. The appointed candidate will be responsible for imparting both theoretical knowledge and practical skills in Statistics and Bioinformatics. This approach guarantees students receive a comprehensive education that trains them to tackle forthcoming challenges in Animal Science and Animal Health. Ultimately, this position significantly contributes to enriching the academic and research landscape of the Faculty of Veterinary Medicine and CIISA.