Research Associate in Machine Learning for Natural Language Processing (NLP)

Job Reference Number: UOS026467
Job Title: Research Associate in Machine Learning for Natural Language Processing (NLP)
Contract Type: Fixed-term for 36 months, or until 30 November 2023, whichever is sooner.
Working Pattern: Full time
Faculty: Faculty of Engineering
Department: Department of Computer Science
Salary: Grade 7 £31,866 – £40,322 per annum with the potential to progress to £44,045 per annum
Closing Date: 5th November 2020

Summary: We are seeking a Research Associate to work in Word Embedding Models, as part of the EPSRC project Modeling Idiomaticity in Human and Artificial Language Processing (MIA), which is a collaboration between the University of Sheffield and University of Cambridge (UK).

MIA is part of the call for Responsible NLP for Intelligent Interfaces, and you will be expected to lead the design and development of strategies for more transparent machine learning models to generate accurate cross-lingual representations for idiomatic language, as well as to contribute to the design and development of resources and evaluation of downstream tasks, like machine translation. For both lines of research, you will build on state-of-the-art approaches based on deep learning. This is an opportunity to work in a well-connected international team with world-leading reputations in the Natural Language Processing (NLP) research group at the University of Sheffield. The NLP group is well known internationally for the excellence of its research, and is one of the largest research groups in computational linguistics and text engineering in the UK. This post offers excellent opportunities for publications, project visits and conference trips.

You must have a PhD (or be close to completion) or have equivalent work experience and a strong publication record. Solid knowledge of Machine Learning models applied to Natural Language Processing and Deep Learning is required, as is excellent programming skills in Python and deep learning frameworks (esp. Keras, TensorFlow or PyTorch). Previous experience developing Word Embedding Models and/or Machine Translation is also desirable. This post is fixed term for a duration of 36 months. However, should the start date be 1 December 2020 or later, the post will have a fixed end date of 30 November 2023. 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.

We believe diversity in all its forms delivers greater impact through research, teaching and student experience. To find out what makes the University of Sheffield a remarkable place to work, watch this short film, and follow @sheffielduni and @ShefUniJobs on Twitter for more information.

Postdoctoral Researcher – Machine Learning applied to Natural Language Processing

Postdoctoral Researcher – Machine Learning applied to Natural Language Processing

Postdoctoral Researcher – Machine Learning applied to Natural Language Processing
Application Deadline: 29.07.2020

The University of Sheffield invites applications for a three-year full-time postdoctoral researcher in Machine Learning applied to Natural Language Processing. The position is part of the EPSRC project on MIA: Modeling Idiomaticity in Human and Artificial Language Processing, a collaboration led by Prof. Aline Villavicencio, Dr. Carolina Scarton, and Prof. Anna Korhonen.

We are looking to make an appointment as soon as possible with a deadline for September 2020 (or as soon as possible thereafter). The initial appointment will be until August 2021, with an extension until at least August 2023. The position is remunerated according to Grade 7 pay scale: £31,866 – £40,322 per annum (with the potential to progress to £44,045 per annum, according to experience).

The responsibility of the postdoctoral researcher is to research strategies for more transparent machine learning models to generate accurate cross-lingual representations for idiomatic language, as well as to contribute to the design and development of resources and evaluation of downstream tasks, like machine translation. The researcher will also be required to collaborate with the University of Cambridge (UK) and the Aix Marseille University (France), partners in this project (there is funding available for short visits to these institutions).

Furthermore,

The ideal candidate will have:
– A PhD in Machine Learning/Natural Language Processing or related field;
– A strong publication record commensurate with career stage;
– Expertise in machine learning (applied to NLP), with experience in the analysis and development of classical and deep learning models;
– Experience in using libraries for NLP and deep learning, such as Tensorflow and Keras;
– Experience in data annotation, data collection, and creating new benchmark datasets for evaluation;
– A willingness to further improve methods skills and to transfer knowledge to doctoral researchers and student assistants.

Expertise in at least one of the following areas is advantageous but not required:
– Track record in ML/NLP methods for developing word embedding models;
– Knowledge of machine translation models.

MIA project: 
MIA is part of the EPSRC call for Responsible NLP for Intelligent Interfaces. In MIA, we will develop idiomatically-aware word/phrase representation models with the ability to process idiomatic (non-literal) language, by incorporating clues that are linguistically-motivated and cognitively-inspired by human processing data. Equipping natural language processing (NLP) models with the ability to process idiomatic expressions is important for obtaining more accurate representations that can lead to gains in downstream tasks, such as machine  translation (MT) and text simplification (TS). MIA targets a crucial limitation in standard NLP models, as idiomaticity is part of human communication, with potential benefits to applications that include natural language interfaces, like conversational agents, question answering and information retrieval systems.

Host institution:
The project is hosted by the Department of Computer Science at the University of Sheffield, a leading international center for research in the UK. We are ranked in the top five for research excellence as part of the 2014 Research Excellence Framework, with 92% of our research outputs being world-leading or internationally-excellent. Our research environment is the best in the country (as measured by the 4* and 3* REF environment score).

The NLP and Speech and Hearing groups have over 60 academics, maintaining an active program of seminars, with exceptional facilities for research, and ample opportunities for collaboration. It is one of the largest and most successful NLP groups in Europe, with multiple worldwide collaborations. Sheffield is a vibrant city with a rich cultural life, with a large number of parks and the Peak District just nearby, perfect for outdoor activities and a high quality of life.

Applications must be submitted using the University of Sheffield system. More information can be found here.

The University of Sheffield is an equal opportunity employer. Applicants from underrepresented minorities are highly encouraged to apply. Remote working arrangements will be discussed upon request. The Department of Computer Science holds a Silver Athena SWAN award, in recognition of our commitment to equality and diversity.

Application Deadline: 29.07.2020

For informal enquiries about this job and the recruiting department, contact: Professor Aline Villavicencio on a.villavicencio@sheffield.ac.uk.
For administration queries and details on the application process, contact the lead recruiter: Marianne Lewis on com-researchrecruitment@sheffield.ac.uk.
For all online application system queries and support, visit: www.sheffield.ac.uk/jobs/applying