Internship Position: Knowledge Discovery: From Unstructured Data to Shared Cognitive Maps

Constructor Knowledge Labs; Bremen; Hybrid; EUR 8.900 - 13.000; Vollzeit

Benefits dieser Stelle

Hybrid or remote options

Zusammenfassung

Constructor Knowledge Labs (CKL) in Bremen, Germany invites applicants for a research internship focused on knowledge discovery and representation, transforming unstructured data into interpretable cognitive structures. The internship is embedded in collaboration with Constructor University and Constructor Technology.

You will help design, implement, and evaluate methods for knowledge representation, semantic structuring, and adaptive reasoning, gaining hands-on exposure at the intersection of

Qualifikationen

• Currently enrolled in a BSc or MSc program in Computer Science, Data Science, AI/ML, or a closely related field.
• Solid programming skills, preferably in Python.
• Basic familiarity with machine learning concepts and data processing workflows.
• Strong analytical thinking and interest in research-oriented work.
• Good written and spoken English.

Aufgaben

• Prepare and organize research data, including text collections, publications, datasets, and related metadata, for analytical tasks.
• Transform unstructured/semi-structured data into structured representations like knowledge graphs or semantic annotations.
• Assist in selected research experiments and analytical tasks under supervision.
• Conduct literature review and support research documentation, with potential contribution to internal reports or publications.

Kenntnisse

Python programming

Analytical thinking

English communication

Ausbildung

BSc or MSc in CS/Data Science/AI/ML

Jobbeschreibung

Constructor Knowledge Labs (CKL), Bremen, Germany

In collaboration with Constructor University and Constructor Technology

Duration: Flexible

About the Position

Constructor Knowledge Labs (CKL) invites applicants for a research internship in the area of knowledge discovery and representation, with a focus on transforming unstructured data into interpretable, navigable, and actionable cognitive structures.

The internship is embedded in an active research direction jointly developed with Constructor University and Constructor Technology, exploring how modern AI systems (particularly large language models and graph-based methods) can be used to construct shared cognitive maps from heterogeneous knowledge sources such as scientific publications, educational materials, and digital artifacts.

The intern will work closely with researchers and engineers on ongoing research activities, contributing to the design, implementation, and evaluation of methods for knowledge representation, semantic structuring, and adaptive reasoning. The position offers hands-on exposure to applied research at the intersection of AI, knowledge graphs, and human-centered knowledge systems.

Main responsibilities:

• Prepare and organize research data, including text collections, research publications, datasets, and related metadata, for use in analytical and modeling tasks.
• Work with unstructured and semi-structured data, supporting its analysis and transformation into structured representations such as knowledge graphs, semantic annotations, or concept mappings.
• Assist in selected research experiments and analytical tasks related to knowledge discovery, reasoning, or information extraction, under supervision.
• Conduct literature review and support research documentation, with potential contribution to internal reports or academic publications.

Requirements:

• Currently enrolled in a BSc or MSc program in Computer Science, Data Science, AI/ML, or a closely related field.
• Solid programming skills, preferably in Python.
• Basic familiarity with machine learning concepts and data processing workflows.
• Strong analytical thinking and interest in research-oriented work.
• Good written and spoken English.

We offer

• Research internship with flexible duration in an international, interdisciplinary research environment.
• Participation in active research projects at the intersection of AI, knowledge systems, and applied research, with a clearly scoped internship-level contribution.
• Close supervision and mentoring by leading PIs and senior researchers, whose work shapes current research agendas and attracts significant scholarly attention and citations.
• Opportunity to contribute to academic publications, embedded in established research groups with consistent presence at top-tier conferences and journals.
• Flexible working arrangements, including hybrid or remote options.

Deadline for full consideration: Applications are reviewed on a rolling basis