Ph.D. Researcher Knowledge Discovery

Beschreibung

Job Zusammenfassung In dieser Position entwickelst du innovative Frameworks für wissensbasierte Systeme, transformierst unstrukturierte Daten in interaktive Wissensgraphen und arbeitest an personalisierten kognitiven Karten sowie adaptiven Informationsmodellen. Job Zusammenfassung In dieser Position entwickelst du innovative Frameworks für wissensbasierte Systeme, transformierst unstrukturierte Daten in interaktive Wissensgraphen und arbeitest an personalisierten kognitiven Karten sowie adaptiven Informationsmodellen. Deine Rolle im Team The research group led by Prof. Dr. Andrey Ustyuzhanin at Constructor University, in collaboration with Constructor Knowledge Labs (CKL) and Constructor Technology (industry partner), invites applications for Ph.D. student positions in the field of Computer Science, with a focus on Artificial Intelligence (AI) and Machine Learning (ML). This PhD position is part of an initiative to advance knowledge representation and adaptive reasoning systems. The research will focus on developing flexible frameworks for actionable knowledge representation that support storage, retrieval, and dynamic adaptation of information across diverse tasks. Key objectives include: Transforming unstructured data into interactive knowledge graphs and personalized cognitive maps. Designing models that provide interpretable, persistent, and navigable structures of knowledge. Addressing challenges such as hierarchy, composability, and coarse-graining for robust, task-specific reasoning. Exploring individual and community-level knowledge modeling, including personalized domain maps, profile extraction from artifacts (e.g., papers, courses), and cross-domain abstraction. The overarching goal is to create systems that enable transparent, adaptive, and spatially intuitive representations of knowledge, supporting both individual users and collaborative communities. Unsere Erwartungen an dich Ausbildung Holding recognized MSc degree (or equivalent) in Computer Science, AI, ML, or a related discipline. Students holding BSc degree and exhibiting outstanding performance and extraordinary potential can apply for fast-track PhD. Qualifikationen A track record of publications in AI/ML or related areas. Strong skills in academic English writing (peer-reviewed papers, reports, or equivalent). Erfahrung Strong mathematical background supported with experience in defining and developing knowledge-graph or information retrieval systems. Hands-on experience with large language models (LLMs) and their applications. Documented experience in practical research work. Unser Angebot 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 €550 mini-job allowance to support parallel part-time employment (optional) Themen mit denen du dich im Job beschäftigst Machine Learning AI Metadaten Level: Erfahren Job Feld: Data Anstellung: Teilzeit Vertragsart: Befristetes Dienstverhältnis Arbeitsmodell: Onsite Unternehmenstyp: Etablierte Firma Branche: Wissenschaft, Forschung Ort: Bremen | Deutschland

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