UVC Partners: Data & AI - Master Thesis / Internship (f/m/x)
About us
What makes us special
How we work
AI-powered development team
Agency matters a lot
Your mission
Potential Research Directions
These are directions we could explore, with scope defined together at the start based on your background and where the work leads.
- With Graph Neural Networks (GNNs) we would work on a graph-structured database, where people and companies are nodes and the relationships between them are part of the data, and ask what that structure can tell us that a table cannot.
- With Program-aided Language Models (PAL) we would have the model write a small program for every number it pulls from decks and financial statements, so figures are accurately computed, because that is what makes it safe to point a language model at financial data.
- And with Bayesian Updating we would keep our recorded understanding of a company moving as new evidence arrives, since the investment process is iterative and a view written down two years ago should not still be the view today. Your thesis could focus on one of these, though as a full-time member of the team you will work across several.
Academic Supervision: The Lead of the Data & AI Team is a PhD candidate at TUM's School of Computation, Information and Technology (CIT) and can supervise CIT masters students directly, so there is no separate supervisor search. However, you are free to choose your own supervisor and candidates from other universities bring their own.
Your profile
- You are enrolled in a Master’s program in Computer Science, Data Science, Data Engineering, Information Systems, or a similar program at a top university.
- You bring depth, or the ambition to build it, in at least one relevant toolkit, whether that is graph ML and graph databases (e.g. PyTorch Geometric), LLM tooling, tool use and evaluation, or probabilistic modeling (e.g. PyMC, NumPyro).
- You write clean, modular Python and have firm machine learning and statistics fundamentals.
- You are fluent with AI-assisted coding tools and you have judgment about them. You know what they do well, where they quietly fail, and you review everything they produce. You do not ship AI slop.
- You work independently. You have run a project where you set the direction yourself, and you can point to it.
- You are fluent in English, including technical language. It is what you will work, write, and present in German is helpful but not required.
What we offer
Network
Team & Culture
Compensation
Ownership
Equipment
AI Tooling
Real Data
Interested?
Diversity is important to us
Contact
Not included in the source posting: what you'll do, qualifications.
Skills
Who can apply
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