Ph.D. Position in Computer Science (Wearable Intelligence & Data Fusion)

Constructor University
Bremen, Germany
4 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English

Job location

Bremen, Germany

Tech stack

Artificial Intelligence
Cognitive Science
Data Fusion
Global Positioning Systems (GPS)
Machine Learning
Signal Processing
Data Streaming
Data Processing
Large Language Models
Information Technology
Multiaccess Edge Computing

Job description

  • 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

Requirements

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

Apply for this position