Research Associate - Sheffield, United Kingdom - University of Sheffield
Description
We are seeking a Research Associate to work with Dr.Nikolaos Aletras (member of the NLP Group) on developing novel methods for analysing the content of online political advertising as part of a larger interdisciplinary project "Understanding online political advertising: perceptions, uses and regulation" funded by the Leverhulme Trust.
This role offers excellent opportunities for publications, project visits and conference trips.You must have a PhD (or be close to completion/have equivalent experience) in Natural Language Processing or related AI fields (for example, Machine Learning, Data Science, Information Retrieval).
You should also have proven track record with publications in top-tier NLP venues (ACL, EMNLP, NAACL, TACL, EACL) and/or related top-tier venues (AAAI, NeurIPS, ICML, ICLR, KDD, WWW, SIGIR, CIKM, ICWSM) commensurate with your career stage.
We're a member of the Russell group and in the top-100 worldwide according to the 2020 QS rankings.The Department of Computer Science (DCS) is a leading research body, being ranked 5th in research excellence out of all UK computer science departments in REF2014, with 92% of its research work was rated either world leading (4*) or internationally excellent (3*) in terms of its originality, significance and rigour.
DCS is a leading centre of research in natural language processing, machine learning and speech processing.The NLP group, established in 1993, is one of the largest and most successful language processing groups in Europe and has a strong global reputation.
We're one of the best not-for-profit organisations to work for in the UK.The University's Total Reward Package includes a competitive salary, a generous Pension Scheme and annual leave entitlement, as well as access to a range of learning and development courses to support your personal and professional development.
We build teams of people from different heritages and lifestyles from across the world, whose talent and contributions complement each other to greatest effect.
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