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Constructor Labs

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

Bremen Posted today

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Machine learningLLMsEnglishTeachingCurriculum development

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No salary bar for this route
H-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.

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About the role

Constructor University in collaboration with Constructor Knowledge Labs and Constructor Technology 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 te

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