Matching Platform for Practice-Oriented Theses

Problem and Background

In Switzerland, over 95,000 academic theses (bachelor’s, master’s, and doctoral) are produced each year, holding substantial innovation potential for the economy. However, this potential often remains untapped as students, companies, and university instructors struggle to connect, despite an active interest from all parties in such networking. Better connections are essential for three reasons: 97% of students do not aim for an academic career but intend to work in industry after graduation; 99.7% of Swiss companies have limited or no access to academic knowledge and highly skilled students; and universities face increasing pressure to align their curricula with societal and economic needs.

Objective of the Research Project

Our research project aims to develop an automated, AI-supported matching platform that enables students to discover practice-oriented thesis topics and directly connect with companies. Companies, in turn, will have the opportunity to post specific topics on the platform, aligned with the concrete challenges they face in the market. This approach allows them to gain access to academic insights and early connections with highly skilled students. Instructors benefit by connecting with industry experts active in their fields of research.

Developing this automated matching platform requires in-depth research and a thorough analysis of the specific needs and requirements of the involved stakeholders. This analysis is crucial for creating a data-driven large language model (LLM) suited for thesis projects, establishing a multidimensional, scalable matching process.

 

For more information, see the project website.

Category

Innosuisse

Reference number

115.877 IP-SBM

Project start

15.05.2024

Project end

14.05.2026

Status

ongoing

Area

Team Leimeister

Problem and Background

In Switzerland, over 95,000 academic theses (bachelor’s, master’s, and doctoral) are produced each year, holding substantial innovation potential for the economy. However, this potential often remains untapped as students, companies, and university instructors struggle to connect, despite an active interest from all parties in such networking. Better connections are essential for three reasons: 97% of students do not aim for an academic career but intend to work in industry after graduation; 99.7% of Swiss companies have limited or no access to academic knowledge and highly skilled students; and universities face increasing pressure to align their curricula with societal and economic needs.

Objective of the Research Project

Our research project aims to develop an automated, AI-supported matching platform that enables students to discover practice-oriented thesis topics and directly connect with companies. Companies, in turn, will have the opportunity to post specific topics on the platform, aligned with the concrete challenges they face in the market. This approach allows them to gain access to academic insights and early connections with highly skilled students. Instructors benefit by connecting with industry experts active in their fields of research.

Developing this automated matching platform requires in-depth research and a thorough analysis of the specific needs and requirements of the involved stakeholders. This analysis is crucial for creating a data-driven large language model (LLM) suited for thesis projects, establishing a multidimensional, scalable matching process.

 

For more information, see the project website.

Persons

Prof. Dr.

Philipp Alexander Ebel

Project manager
To Detail
Prof. Dr.

Philipp Alexander Ebel

Project manager
To Detail
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