|Salary:||£35,333 to £46,047 per annum (Grade 7)|
|Placed On:||5th August 2022|
|Closes:||1st September 2022|
Contract type: This post is fixed-term for 36 months if start date is before 1st November 2022. If the start date is after 1st November 2022, then the post has a fixed end date of 31st October 2025.
The Department of Computer Science was established in 1982 and has since attained an international reputation for its research and teaching. In the 2014 Research Excellence Framework (REF) exercise, we were ranked 5th out of 89 departments in the UK for computer science research. Much of our research spans the boundaries between engineering, medicine and the life sciences. Research in the Department is organised into a number of groups: Machine learning, Algorithms, Complex systems modelling, Natural language processing, Speech and hearing, Organisations, information and knowledge (OAK), Verification and testing, Visual computing, and Security of Advanced Systems. We attract substantial external funding from UK Research Councils, the European Union and industry. Our record for leadership in collaborative research is outstanding, particularly in European programmes. The Department is currently host to two ERC fellows and three EPSRC fellows. More information on the Department of Computer Science can be found at www.shef.ac.uk/dcs.
We welcome applications for a three year postdoctoral Research Associate position in the area of natural language processing and machine learning, and more specifically analysis of online misinformation. The main focus of the post-holder will be research on explainable machine learning methods for detection and analysis of online misinformation. The post holder will carry out the studies on real-world misinformation around COVID-19, the war in Ukraine, and election misinformation. The successful candidate will be able to demonstrate knowledge and experience in this topic and in writing high-quality research papers.
You will hold a PhD in Natural Language Processing/Machine Learning or a related area with a solid research background.
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