Ph.D. Position (m/f/d) in Computer Science (Wearable Intelligence & Data Fusion)

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 ofDr. Sari SadiyaatConstructor Knowledge Labs (CKL), in collaboration withConstructor University (CU)andConstructor Technology (CT), invites applicants forPh.D. student positionsin Computer Science with a focus onwearable 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, combiningAI/ML, edge computing, cognitive science, and human–computer interaction. In close collaboration with academia and industry, they will contribute to buildingprivacy-preserving, real-time personalization frameworkswhile 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 withConstructor Technologyto gain first-hand industrial experience, contributing to real-world testbeds and prototypes.

Research Focus

This PhD position is part of theWearable 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 theAgentic 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 runningcompact micro-LLMs directly on wearables.

The overarching goal is to createscalable, ethical, and transparent personalization systemsthat 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 withwearable 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 withLLMs, multimodal data fusion, or agent-based AI systems.

• Familiarity withprivacy-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.