PostDoc Position Available in Conversational Search

We are seeking a Postdoctoral Research Fellow that will contribute to innovative research developments within the scope of conversational search. The project the postdoc will be assigned to aims to identify how conversational agents might help answer grain growers and farmers’ questions and make better farming decisions. The position is part of the newly funded research project AgAsk that involves researchers at the University of Queensland, the CSIRO, and the Queensland Government Department of Agriculture and Fisheries.

Project Description

Valuable grains R&D output is currently locked away into project reports, communications and scientific publications. This text-based information is not easily discoverable and synthesised. Thus growers are not able to put into practice these valuable insights. This project will develop a conversational agent (AskAg) that will provide personalised access to this valuable information leading directly to better, data-driven growing decisions. Through question-answering systems, AgAsk will elicit and understand growers information needs and preferences, providing contextualised access to insights in Ag R&D. AgAsk will use state-of-the-art IR, NLP and ML technology to interpret natural language questions. Ag R&D resources will be mined from textual information and converted into a knowledge graph capturing key agricultural concepts and relations (e.g. protozoa –effective_for–> control of pest molluscs). AgAsk will use this knowledge graph to formulate contextualised and interpretable answers to a growers question (e.g. via abstractive summarisation and answer generation).

The successful applicant will enrol through the School of Information Technology and Electrical Engineering at The University of Queensland (UQ), and will be a member of the ielab team (www.ielab.io), within the UQ Data Science discipline.

The Data Science discipline researches and develops innovative and practical solutions for business, scientific and social applications in the realm of big data. The group encompasses a variety of research strengths including: Data and knowledge engineering, Information Retrieval, Computer Vision, and Complex and Intelligent Systems. You will join a world-leading research group currently composed of 13 academic staff members (including 4 full professors, two DECRA fellows and an Advanced Queensland Fellow), 7 research fellows and over 40 PhD students. Members of the group have a successful track record of publishing in top conferences and journals such as ACM SIGIR, ACM CIKM, The Web Conference (WWW), SIGMOD, VLDB, ICDE, ICDM, KDD and various ACM and IEEE transactions.

The research environment available to the project is world-class. The University of Queensland (UQ) has a strong and internationally focused research culture. It is ranked in the top 1% of world universities in three widely publicized international University rankings. The areas of research in these PhD projects have a strategic fit within UQ’s existing research strengths in Data Science.

Brisbane is a liveable, capital city with great weather, vibrant green spaces, lively bars and restaurants, world-class art galleries and premier events. It is the third most populous city in Australia and is closed to premier recreational locations such as the Sunshine Coast and the Gold Coast.

Successful applicants should possess a PhD in the field of Information Retrieval, Natural Language Processing, or Machine Learning on Textual Data.

You should have demonstrated expert knowledge in relevant empirical research methods, including Knowledge Graph creation, question answering, answer generation and ranking, abstractive summarisation, interactive information retrieval, intent understanding, user-based evaluation (evaluation of IR systems with users). Research experience with conversational search and conversational agents, domain-specific search, and task-based retrieval will be beneficial and highly regarded. You would have a demonstrated publication record in quality research outlets in relevant fields; examples include ACM SIGIR, ACM WSDM, The Web Conf, ACL, NAACL-HLT, EMNLP, AAAI, ACM TOIS, ACM TIST, TACL. You would also have showcased ability to successfully work in a research team to deliver outputs to industry and outstanding effective communication and interpersonal skills.