Enabling inorganic growth through a fully digitized target search platform

Results of this project will be shown here by the end of September 2023

Apply to this project here

Infineon is a world leader in semiconductor solutions that make life easier, safer, and greener. Our solutions for efficient energy management, smart mobility, and secure, seamless communications link the real and the digital world. Infineons Strategy, Mergers & Acquisitions Department leverages Artificial Intelligence for target searches for future acquisitions.

In our TUM Data Innovation Lab project we are looking for highly motivated students who enjoy working at the intersection of AI and strategic business-decision making and market analysis. You will support the development of an automized, deployable, end-to-end target search process using natural language processing (NLP). With each target search the algorithm is continuously trained and improved to ultimately understand Infineon strategy. A database shall be connected at the end of the process in order to collect, monitor and track progress on most relevant companies identified. The vision is to implement an end-to-end process that allows M&A project managers to have an efficient tool for conducting target searches, reducing time required from months to weeks and to allow for a shared platform that can be used by M&A and business experts to assess companies live. Ultimately the platform will also serve as a reporting tool / dashboard for top management.  


The project will provide you with experience on using AI for corporate strategy and decision-making. You will be part of a driven team of business and technical experts as well as a NLP focused start-up from Berlin.
Your tasks will include:
•    Developing an automized, end to end process flow
•    Embedding the existing NLP algorithm into the process flow allowing for feedback loops
•    Further model optimization by training the algorithm based on existing datasets
•    Evaluate how crawled data may boost performance of an algorithm
•    Develop UI / UX for visualization throughout the process and reporting
•    Establish a connection to a CRM-like database for archiving prioritized companies
Accepted students should familiarize themselves with Haystack (github), an open source NLP framework that leverages pre-trained Transformer models.

 

Important notice

Accepted students to this project should attend online workshops at the LRZ in April 2023 before the semester starts, unless they have proven knowledge. More information will be provided to students accepted to this project.