PhD scholarship in AI-Augmented Sense-Making in Digital Phenotyping - DTU Health Tech

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

We are looking for an ambitious PhD student to work at the intersection of digital health, artificial intelligence, large language models (LLMs), and human-computer interaction. The PhD project, SCALE – AI-Augmented Sense-Making of Large-Scale Population-Based Digital Phenotyping Datasets, will investigate how LLMs and interactive AI can help researchers explore complex health data collected from smartphones and wearables. The goal is to develop an interactive environment where researchers can use natural language to explore and visualize multimodal data, identify patterns and anomalies, and iteratively develop hypotheses in collaboration with AI. The project will use real-world data from the Copenhagen Research Platform (CARP), including an ongoing nationwide study of cognition and mental health. You will collaborate with researchers at DTU and at Eindhoven University of Technology (TU/e), which hosts a related "sister" PhD project.

Responsibilities and tasks

Your main responsibility will be to develop and evaluate new methods and interactive technologies for AI-augmented exploration of large-scale digital phenotyping data. You will:

• Study how health researchers explore complex multimodal datasets and identify their 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 where AI assists in identifying patterns, anomalies, and hypotheses while keeping researchers in control.
• Work with large-scale CARP datasets containing smartphone, wearable, behavioral, physiological, and self-reported data.
• Evaluate the developed methods with researchers, focusing on usability, efficiency, explainability, and trust.
• Collaborate with the sister PhD project at TU/e, including a research stay, joint development, and scientific publications.

Qualifications

You must have a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree.

• A master's degree in computer science, data science, AI, health technology, biomedical engineering, HCI, or a related field.
• Strong programming skills and experience with data science and machine learning.
• Experience with LLMs, generative AI, and AI-supported data analysis.
• Experience in data visualization, human-AI interaction, and explainable AI.
• Interest in working with large, heterogeneous datasets from smartphones and wearables.
• Ability to design and implement research prototypes and conduct empirical evaluations.
• Good communication and scientific writing skills in English and the ability to work in an interdisciplinary, international team.

Experience with digital health, digital phenotyping, time-series analysis, visual analytics, HCI/user studies, or mobile and wearable sensing is an advantage.

Approval and Enrolment

The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see DTU’s rules for the PhD education.

We offer

DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility.

Salary and appointment terms

The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. Please see DTU’s salary structure for scientific staff: www.inside.dtu.dk/en/human-resources/during-employment/salary/salary-structures. The period of employment is 3 years. The position is full-time, with a starting date of 1 January 2027 or according to mutual agreement.

Further information

Further information may be obtained from Jakob Bardram ([e-mail]). You can read more about Prof. Bardram's research at www.bardram.net/. You can read more about the Department of Health Technology (DTU Health Tech) at www.healthtech.dtu.dk. If you are applying from abroad, you may find useful information on working in Denmark and at DTU at DTU – Moving to Denmark. Furthermore, you have the option of joining our monthly free seminar “PhDrelocation to Denmark and startup “Zoom” seminar” for all questions regarding the practical matters of moving to Denmark and working as a PhD at DTU.

DTU Health Tech engages in research, education, and innovation in technical and natural sciences for the healthcare sector. The healthcare sector is a globally expanding market with demands for the most advanced technological solutions. DTU Health Tech lays the foundation for companies to develop innovative products and services that benefit people and create value for society. DTU Health Tech’s expertise spans imaging and biosensor techniques, digital health and biological modeling, and biopharma technologies. The department has a scientific staff of about 210 persons, 130 PhD students, and a technical/administrative support staff of about 160 persons, the majority of whom contribute to our research infrastructure and related commercial activities.

DTU – For the benefit of society since 1829. DTU is one of Europe's leading elite technical universities. Through research and education at an international top level, we create solutions to the major societal challenges of our time and help secure Europe's global leadership in sustainable technological development. Since Hans Christian Ørsted founded DTU almost 200 years ago, our mission has remained the same: We develop and create value through the natural and technical sciences for the benefit of society. DTU has 13,800 students, 1,600 PhD students, and 6,500 employees. We work in an international environment and have an inclusive, stimulating, and informal work culture. DTU has campuses in all parts of Denmark and in Greenland and collaborates with the best universities around the world.

All interested candidates irrespective of age, gender, disability, race, religion or ethnic background are encouraged to apply. As DTU works with research in critical technology, which is subject to special rules for security and export control, open-source background checks may be conducted on qualified candidates for the position.