An experienced and motivated postdoctoral scientist is sought to join the Kyriazakis Quantitative Animal and Veterinary Science Group at the School of Biological Sciences of Queen's University Belfast. The successful candidate will undertake a senior role in the planning and delivery of research activities focused on assessing the interconnections between inputs and outputs in beef cattle and sheep systems in relation to animal health by using AI tools. The The cross-disciplinary Group consists of members with skills in veterinary and animal science, sustainability assessment, and data and computer sciences, and focuses on the development and application of transformative technologies for, and the quantitative assessment of their impacts on the sustainability of livestock systems. This particular role addresses the latter, as the job holder will be expected to develop methods and apply them for the Surveillance and Early Warning for Emerging Threats in Livestock using Artificial Intelligence. The post is aligned with SENTINEL, a collaborative project between the leading agricultural and veterinary Institutions on the island of Ireland (University College Dublin, AgriFood and Bioscience Institute,Teagasc). The successful candidate will have a demonstrable track record in Data Science with an excellent PhD degree awarded and strong publication record. The successful candidate will have responsibilities in independent research, supervision, planning, day-to-day lab management, collaborations and outreach. The successful candidate must have, and your application should clearly demonstrate that you meet the following essential criteria: Have or about to obtain* a PhD in Data Science or a related discipline (*must be obtained within 3 months of commencement of employment). Significant relevant research experience in data mining and fusion, and dealing with large datasets that may contain potentially noisy, structured or unstructured data. Experience in Machine Learning and in programming languages such as Python, C++ or Go. Experience in statistical methodology, dealing with epidemiological approaches to the interconnectivity of inputs and outputs in livestock systems. Peer reviewed publications or preprints in the area of Data Science, including first author ones. This is not an exhaustive list. To be successful at shortlisting stage, please ensure you clearly evidence in your application how you meet the essential and, where applicable, desirable criteria listed in the Candidate Information on our website. This post is available for 35 months or until 31 March 2029, whichever is soonest. Fixed term contract posts are available for the stated period in the first instance but in particular circumstances may be renewed or made permanent subject to availability of funding. TLNT1_NI
