Research Assistant

• Acting as secretary to undergraduate and postgraduate Faculty Assessment Boards, Module Assessment Sub Boards of Examiners, and Appeal Boards, and to support the servicing and organisation of a large volume of Faculty Assessment Board meetings.
• Ensuring that meetings attended are conducted in accordance with the College regulations and that decisions made at those meetings are recorded and communicated as appropriate.
• Providing support and guidance to Faculty Assessment Board and Assessment Sub Board Chairs, with regard to assessment regulations. 
• Preparing and distributing documents for Faculty Assessment Board meetings.
• Liaising with a range of stakeholders, including academic colleagues, to maintain key data sets and files. 
• To respond to queries related to a comprehensive enquiry service for members of academic staff, administrative staff and students, either on the telephone, in writing or in person.

• Educated to Degree Level or Equivalent

• Excellent administrative skills, with high attention to detail. 
• Experience of committee servicing.
• Understanding of regulatory issues in a Higher Education context.
• Ability to develop, articulate and implement policies and procedural systems.
• A proven ability to organise, and plan ahead effectively.
• Good interpersonal, communication and presentation skills.
• Ability to work collaboratively with a variety of stakeholders.
• Knowledge of policies and procedures and their application in a Higher Education context. 
• Experience of working in Higher Education.
• Experience of minute-taking and servicing meetings.
• Experience of providing guidance and training on complex policies and procedures, to a wide range of audiences. 
• Experience of compiling and interpreting management information. 
• Sound knowledge of Microsoft Office suite including MS Word, Excel, PowerPoint, Teams, SharePoint and Outlook and ability to learn new systems quickly and competently.

Job Title: Research Assistant ? Benchmarking Large Language Models (LLMs) in Clinical Question-Answering

Project Overview: We are seeking a motivated and detail-oriented Research Assistant to support our research project focused on benchmarking Large Language Models (LLMs) in real-world clinical question-answering tasks. The project involves creating high-quality clinical datasets and systematically evaluating the performance of various LLMs to determine their efficacy and accuracy in clinical decision-making scenarios.

Responsibilities:

Assist in the design, creation, and curation of clinically relevant question-answer datasets derived from real-world clinical scenarios.

Perform systematic literature reviews to identify relevant benchmarks and metrics in clinical NLP evaluations.

Conduct model evaluations, including running experiments, data preprocessing, and analyzing model outputs.

Document experimental results and contribute to writing research reports and scientific papers.

Collaborate closely with the research team to ensure data integrity and methodological rigor.

Bachelor's or Master's degree in Computer Science, Data Science, Biomedical Informatics, Computational Linguistics, or a related field.

Skills:

Bachelor's or Master's degree in Computer Science, Data Science, Biomedical Informatics, Computational Linguistics, or a related field.

Prior experience or coursework in Natural Language Processing (NLP), Machine Learning (ML), or Healthcare Informatics.

Familiarity with Python and ML frameworks/libraries (e.g., Hugging Face, PyTorch, TensorFlow).

Strong organizational, analytical, and communication skills.

Ability to work independently and collaboratively in an academic research environment.

Preferred Experience:

Previous experience working with clinical datasets or clinical NLP projects.

Experience evaluating language models (e.g., GPT models, BERT).

Understanding of clinical terminologies (e.g., SNOMED, ICD-10, UMLS).

Supervising COMPASS-MS 2 hours a week for 

DclinPsych

Existing clinical psychologist expertise