At a Glance
- Tasks: Lead innovative research using AI to enhance livestock health and sustainability.
- Company: Join a top-tier university's dynamic research group focused on animal science.
- Benefits: Competitive salary, collaborative environment, and opportunities for professional growth.
- Other info: 35-month contract with potential for extension; perfect for passionate researchers.
- Why this job: Make a real impact in agriculture with cutting-edge data science techniques.
- Qualifications: PhD in Data Science or related field, strong research and programming skills required.
The predicted salary is between 35000 - 45000 £ per year.
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 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.
Research Fellow in Data Science in Belfast employer: Queens University
Queen's University Belfast offers an exceptional work environment for the Research Fellow in Data Science, fostering a collaborative culture that encourages innovation and interdisciplinary research. With access to cutting-edge technologies and a focus on sustainability in livestock systems, employees benefit from professional growth opportunities, including involvement in high-impact projects like SENTINEL. The university's commitment to academic excellence and community engagement makes it an attractive employer for those seeking meaningful contributions to animal health and data science.
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We think you need these skills to ace Research Fellow in Data Science in Belfast
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Craft a Tailored Cover Letter:For a full-time role at Queens University, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Queens University. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Queens University
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
