Postdoctoral Research Assistant or Research Assistant

Opportunity ID  

3503

Faculty   Science & Engineering Location   QM London Contract Type   Fixed Term Duration   41 Months (or until 31 March 2028, whichever is sooner) Working Patterns   Full Time

Full Time Equivalent (FTE)

 

1.00

Working Hours (Per Week)   35.00 Salary Range   Grade 4 through 5 £40,223- £44,722 per annum for PDRA and Grade 4 £36,572 - £37,182 per annum for RA Job Pack   3503 - RA & PDRA Job Profile.pdf – 9864KB Opens in a new window Contact Details   Informal enquiries should be addressed to m.liakata@qmul.ac.uk. Details about the School can be found at www.eecs.qmul.ac.uk About the Role  

School of Electronic Engineering and Computer Science (EECS)

 

Postdoctoral Research Assistant or Research Assistant

About the Role

We are pleased to offer a Postdoctoral Research Assistant or Research Assistant post under the supervision of Prof Maria Liakata, in the context of the RAi UK/UKRI funded Keystone project on Addressing socio-technical limitations of Large Language Models (LLMs), particularly for medical and social computing (https://adsolve.github.io/). The role involves developing methods for better evaluation of LLMs for real world scenarios, augmenting LLMs with temporal reasoning and the ability to perform longitudinal predictions with multi-modal data, mitigation for hallucinations and biases. For details see the project website and in particular workstreams 2,3 and 5.

About You

Candidates must have an Undergraduate Degree in Computer Science or a related topic. Applicants at the PDRA level must have a PhD in NLP or machine learning. Substantial knowledge of Natural Language Processing (NLP) and machine learning methods is essential, as well as good understanding of work in model explainability, LLM fine tuning and evaluation. Experience in working on explainability of NLP and machine learning models is desirable.

About the School of EECS

Our researchers work with the arts and sciences collaborating with psychologists, biologists, musicians and actors, mathematicians, medical researchers, dentists and lawyers. As a multidisciplinary School, we are well known for our pioneering research and pride ourselves on our world-class projects. We are equal first in the UK for the impact of our Computer Science research, and second in the country for our Electronic Engineering research output (REF 2021).

About Queen Mary

Throughout our history, we have fostered social justice, improved lives through academic excellence, and we continuously embrace diversity of thought in everything we do. We believe that when views collide, disciplines interact, and perspectives intersect, truly original thought takes form.

Benefits

We offer competitive salaries, pension scheme, 30 days’ leave per annum, a season ticket loan scheme and access to a comprehensive range of personal and professional development opportunities. In addition, we offer a range of work life balance and family friendly, inclusive employment policies, flexible working arrangements, and campus facilities including an on-site nursery at the Mile End campus.

The post is based at the Mile End Campus in London. It is a full time (35 hours per week), fixed term appointment for 41 months (or until 31 March 2028, whichever is sooner) and is expected to start from November 2024. The starting salary will be in the range of Grade 4 through 5 (£40,223- £44,722) for PDRA and Grade 4 (£36,572 - £37,182) for RA per annum inclusive of London Allowance.

Queen Mary’s commitment to our diverse and inclusive community is embedded in our appointments processes. Reasonable adjustments will be made at each stage of the recruitment process for any candidate with a disability. We have policies to support our staff throughout their careers, including arrangements for those who wish to work flexibly or on a job share basis, and we provide support for those returning from long-term absence. We particularly welcome applications from under-represented (BAME) groups, and from women in all stages of life, including pregnancy and maternity leave.

Candidates are kindly requested to upload documents totaling no more than 10 pages; certificates, references and research papers should not be provided at this stage.

Closing Date  

10/10/2024, 23:55