The National Institute of Education invites suitable applications for the position of Research Assistant on a 12-month contract at the English Language and Literature department.

Project Title: Train Your Dragon: Fine-tuning Large Language Models to Create Agentic AI for Automatic Assessment Generation

Project Introduction:

This position involves two closely related research strands at the intersection of language assessment and artificial intelligence. The first focuses on developing agentic AI systems to support the automated construction and evaluation of language tests. This includes fine-tuning large language models (LLMs) for tasks such as item generation, test assembly, and automated essay scoring, with an emphasis on validity, reliability, and methodological transparency.

The second strand centers on advancing LLM-based spoken dialog systems integrated with sensor technologies, including neuroimaging and eye-tracking. Building on our existing in-house platform, the research assistant will extend system capabilities to address emerging research questions related to cognitive load, interaction dynamics, and adaptive dialogue management. This role requires both technical development and empirical research, contributing to innovative approaches in technology-enhanced language assessment.

A. Required background and skills

Bachelor's degree in computer science, artificial intelligence, data analytics, computational psychology, or a closely related field
Demonstrated experience with large language models (LLMs), including fine-tuning, APIs, or related methods for text generation or evaluation tasks
Programming proficiency in Python (knowledge of R is an advantage)
Experience developing agentic AI systems using LLM APIs/SDKs, including tool use, orchestration, and workflow design
Proficiency in one or more of the following areas: natural language processing (NLP) and/or speech technologies (e.g., ASR, TTS, dialog systems)
Reliable background in quantitative and computational methods
Working understanding of experimental research design and data analysis

B. General competencies

Strong motivation for interdisciplinary research and ability to work collaboratively in a team environment
Strong teamwork skills, openness to innovative ideas, and intellectual curiosity
Resilience and persistence in tackling complex research and development challenges
Excellent written and verbal communication skills in English

C. Preferred

Experience with automated item generation, automated essay scoring, or educational measurement applications of AI
Familiarity with spoken dialog systems or conversational AI development
Familiarity with sensor-based research methods (e.g., EEG, fNIRS, eye tracking)-training will be provided
Familiarity with neurofeedback and human-computer interaction (HCI) methods
Experience working with multimodal data (e.g., speech, text, physiological signals)
Prior involvement in interdisciplinary projects combining AI, language, and cognitive science
Experience contributing to academic publications or conference presentations

Responsibilities:

Develop and fine-tune LLMs for language assessment applications, including automated item generation, test assembly, and automated essay scoring
Design and implement agentic AI systems using LLM APIs/SDKs, including tool integration, workflow orchestration, and iterative model improvement
Contribute to the development and extension of in-house spoken dialog systems for research and experimental use
Integrate and manage multimodal data streams (e.g., speech, text, neuroimaging, eye tracking) within dialog system architectures
Support the design and implementation of experimental studies involving human-AI interaction and sensor-based data collection
Analyze and interpret quantitative and multimodal datasets using appropriate statistical and computational methods
Collaborate with interdisciplinary team members across AI, language assessment, and cognitive science domains
Contribute to the preparation of research outputs, including conference papers, journal articles, and technical reports
Document code, models, and experimental procedures to ensure reproducibility and scalability
Assist in maintaining and improving research infrastructure, including codebases, APIs/SDK integrations, and experimental platforms
Any other duties as assigned by the Principal Investigator

Application

Applicants (external and internal) will apply via Workday. We regret that only shortlisted candidates will be notified.

Closing Date

Closing date for advertisements will be set to 14 calendar days from date of posting.

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