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Constructor University in collaboration with Constructor Knowledge Labs and Constructor Technology invite applications from interested candidates for the following position

PhD Position (m/f/d) in Computer Science (Wearable Intelligence & Data Fusion)

About the Position

The research group of Dr. Sari Sadiya at Constructor Knowledge Labs (CKL) , in collaboration with Constructor University (CU) and Constructor Technology (CT) , invites applicants for Ph.D. student positions in Computer Science with a focus on wearable intelligence, multimodal data fusion, and edge AI .

The project investigates how wearable data streams can be transformed into structured knowledge and integrated into a knowledge-grounded digital avatar that supports bi-directional collaboration in education and research.

Ph.D. students will work in a highly interdisciplinary environment, combining AI/ML, edge computing, cognitive science, and human–computer interaction . In close collaboration with academia and industry, they will contribute to building privacy-preserving, real-time personalization frameworks while pursuing their doctoral dissertation.

About the Program

The PhD program is research-centered, emphasizing original contributions in:

Wearable data analytics and fusion methods
Biomedical data analytics
On-device processing and performance modeling
Personalization and adaptive reasoning systems
AI for Education

Doctoral students will also have access to specialized courses in:

Artificial Intelligence, Machine Learning, and Edge Computing
Advanced Computational Methods and Data Science
Cognitive Science and Human-Centered Computing

As part of the program, students will collaborate with Constructor Technology to gain first-hand industrial experience, contributing to real-world testbeds and prototypes.

Research Focus

This PhD position is part of the Wearable Intelligence Project , with two main research directions:

Data fusion of heterogeneous temporal streams
- Designing algorithms to unify multimodal signals (physiological, cognitive, contextual, scheduling, and learning data).
- Developing pipelines that produce structured insights powering the Agentic Personalization Engine (APE) .
On-device data processing & performance modeling
- Developing models balancing computation, energy, and data flows across wearable, edge, and cloud environments.
- Exploring feasibility of running compact micro-LLMs directly on wearables .

The overarching goal is to create scalable, ethical, and transparent personalization systems that support education and research.

Funding

The appointment provides full financial coverage through a dedicated fellowship, comprising:

Monthly stipend of €1,650
Monthly research-cost allowance of €100 (Forschungskostenpauschale)
Health-insurance subsidy of €100 per month
Supplementary €603 mini-job allowance to support parallel part-time employment (optional)

Constructor Knowledge Labs actively supports candidates in preparing applications for external funding — doctoral scholarships, foundations, or international mobility grants — and can provide institutional support and references

Applicant Profile

Mandatory requirements:

MSc degree (or equivalent) in Computer Science, AI/ML, Data Science, Cognitive Science, or related disciplines.
Strong background in AI/ML, signal processing, or edge computing.
Hands-on experience with wearable or multimodal data (e.g., heart rate, EEG, activity, sleep, GPS) .
Solid mathematical and computational modeling skills.
Proficiency in academic English writing (e.g., reports, papers, theses).

Preferred qualifications:

Experience with LLMs, multimodal data fusion, or agent-based AI systems .
Familiarity with privacy-preserving ML, dynamic consent, and GDPR-compliant frameworks .
Demonstrated ability to conduct independent research and collaborate across disciplines.
Interest in teaching, mentoring, and applied industrial research.

Application Details

Deadline : August 31, 2026

Required documents:

Curriculum Vitae (CV);
Academic transcripts;
Letter of motivation outlining research interests and career goals;
2 recommendation letters.

Applications to be reviewed on a rolling basis. Shortlisted candidates will be invited to interviews.

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