Internship Position: Grant Intelligence Pipeline & Research Opportunity Modeling

Location: Bremen, Germany

Constructor Knowledge Labs (CKL), Bremen, Germany

In collaboration with Constructor University and Constructor Technology

Duration: Flexible; starting date as soon as possible

Constructor Knowledge Labs (CKL) invites applications for a research-oriented internship. This project focuses on building an internal, scalable system that continuously discovers funding opportunities, structures and evaluates them, and supports strategic decision-making through data-driven insights.
The internship will contribute to the development of a multi-stage pipeline that integrates data collection, information extraction, profile matching, and analytical modeling. A key research direction includes exploring predictive approaches to estimate the probability of success (“Probability of Win”) for grant applications.
The role provides hands-on exposure to real-world challenges in information retrieval, data structuring, decision-support systems, and applied machine learning within a research-driven environment.

• Assist in the development of automated pipelines for discovering grant opportunities from multiple sources.
• Support parsing, cleaning, and structuring of unstructured grant texts into standardized formats.
• Contribute to building and maintaining institutional and researcher profile datasets.
• Help design and implement scoring mechanisms (e.g., Fit Score).
• Participate in exploratory data analysis and prototyping of analytical components.
• Support development of dashboards, reporting tools, or notification systems.
• Conduct literature reviews on relevant topics.
• Assist in exploration of predictive models for estimating grant success probability.
• Document workflows and experimental findings.

• Currently enrolled in a Bachelor’s or Master’s programme in a relevant field;
• Basic programming skills (e.g., Python).
• Understanding of data analysis, statistics, or machine learning concepts.
• Interest in data-driven systems and automation.
• Strong analytical thinking.
• Good written and spoken English.

• 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.

Please submit:

• CV
• Motivation letter (max. 1 page)
• Transcript of records (GPA obligatory)

Deadline: 30 August 2026, 23:59 CET