Research Assistant

Job Description

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).