PhD: AI-Driven Exploration of Digital Health Data

DTU; Denmark; Remote; DKK 360,000 - 480,000; Full time

Job summary

DTU Health Tech in Denmark invites applications for a PhD student position in SCALE, an AI-augmented sense-making project on large-scale digital phenotyping datasets. You will develop interactive AI-enabled tools to translate natural language queries into data analyses and visualizations, enabling researchers to explore multimodal health data from smartphones and wearables.

You will collaborate with DTU researchers and TU/e, perform empirical evaluations, and contribute to publications while

Qualifications

• Master's degree or equivalent at academic level
• Strong programming skills and ML experience
• Experience with LLMs and generative AI
• Experience in data visualization and human-AI interaction
• English writing skills and ability to work in an interdisciplinary team

Responsibilities

• Develop and evaluate new methods and interactive technologies for AI-augmented exploration of large-scale digital phenotyping data
• Study researchers' analytical needs and workflows
• Design and implement an LLM-based environment translating natural-language questions into data queries, analyses and visualizations
• Investigate human-AI interaction to assist in identifying patterns while keeping researchers in control
• Collaborate with the sister PhD project at TU/e and participate in dissemination activities

Skills

Programming

Data science & ML

LLMs / Generative AI

Data visualization

HCI / Human-AI interaction

Empirical evaluation

English writing

Education

Master's degree (2-year) in CS/Data Science/AI or related

Tools

Python

Job description

DTU Health Tech in Denmark invites applications for a PhD student position in SCALE, an AI-augmented sense-making project on large-scale digital phenotyping datasets. You will develop interactive AI-enabled tools to translate natural language queries into data analyses and visualizations, enabling researchers to explore multimodal health data from smartphones and wearables.

You will collaborate with DTU researchers and TU/e, perform empirical evaluations, and contribute to publications while