Research Associate in Speech and Multimodal Data Analysis for Mental Health
- A PhD (or equivalent) in a relevant discipline (e.g., biostatistics, machine learning, computer science, clinical informatics, natural language processing).
- Strong skills in data analysis and programming (e.g., Python or R).
- A track record of publications in high -quality scientific journals.
- Experience or interest in large language and foundational models is an advantage.
- PhD or equivalent in a relevant discipline (e.g., biostatistics, computer science, clinical informatics, natural language processing).
- Proven experience in speech and language analysis, including acoustic feature extraction and/or natural language processing (NLP) techniques.
- Proficiency in data analysis and programming with languages such as Python or R.
- Experience handling and integrating large, complex datasets, including multimodal data
- Proven track record of writing and publishing scientific papers in high-impact journals.
- Experience with Large Language Models (LLMs) or other foundational models applied to speech or text data
- Experience applying speech and language technology in mental health research, particularly in depression
- Familiarity with wearable technologies, including data cleaning and feature extraction
- Experience in grant writing and securing research funding.
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