UVC Partners: Data & AI - Master Thesis / Internship (f/m/x)

UnternehmerTUM gGmbH · München Kreativquartierjunior

En corto

▸Trabajo de tesis o pasantía en inteligencia de inversiones con IA, al lado de inversores y científicos de datos.
▸Días típicos: investigar problemas reales, construir prototipos con GNNs, PAL o actualización bayesiana, y presentar hallazgos a inversores.
▸Se trabaja con IA como herramienta principal, con enfoque en autonomía, crítica y prototipado rápido.

Fluent English required for collaboration and presentation.

En ~1 minuto te damos: quién te entrevista, las preguntas probables con respuestas desde tu CV, y tu CV adaptado a esta vacante. Gratis, sin tarjeta.

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¿Qué piden?

✓Estudiante de máster en Ciencia de Datos, Informática o áreas afines en una universidad reconocida.
✓Profundidad o interés en al menos una de: ML de grafos, modelos de lenguaje con herramientas, modelado probabilístico.
✓Capacidad para trabajar de forma autónoma, proponer enfoques y revisar resultados de IA.
✓Experiencia con herramientas como PyTorch Geometric, PyMC, NumPyro, o similares.
✓Inglés avanzado para comunicación y documentación técnica.
✓Disponibilidad para trabajo full-time durante la pasantía.

¿No cumplís todo? Es lo normal — tu dossier gratis te dice qué gaps tenés y cómo cubrirlos en la entrevista.

Graph Neural NetworksProgram-aided Language ModelsBayesian UpdatingPyTorch GeometricLLM toolingPyMCNumPyroGraph databasesFinancial data analysisAI-assisted coding

¿A quién escribirle en UnternehmerTUM gGmbH?

Tu dossier gratis identifica a las personas que te entrevistarían — con su background, qué valoran y cómo escribirles para destacar antes de aplicar.

About us UVC Partners is one of Europe’s leading early-stage venture capital firms. With our fourth fund generation of €250 million, we invest in disruptive B2B startups at the seed and Series A stage across Europe. Our focus areas include enterprise software, mobility, and industrial technologies. auto, Proxima Fusion, and Aleph Alpha. What makes us special At UVC Partners, we’re driven by a deep passion for entrepreneurship and its power to positively shape society. Environmental and social responsibility are core to our DNA. We hold ourselves to the highest standards in everything we do. As a firm, we continuously reinvent ourselves to stay ahead and best serve our portfolio and investors. We believe in ownership over hierarchy and foster a culture built on collaboration, curiosity, and personal engagement. And while we’re serious about our mission, we also genuinely enjoy working together and building lasting relationships along the way. How we work We are an AI-powered development team . Everyone here codes with AI assistance, and we treat that as a craft. You need to know which parts of a problem to hand over, where these tools fail quietly, and how to review output you did not write. Agency matters a lot in our team. You get mentorship, context, and access to everyone. You do not get someone assigning you tasks every morning. Take a rough problem statement, come back with an approach, show drafts while they can still change, and flag what is not working. What you bring should outweigh what it costs us to support you. Your mission You will join a specialized team working at the intersection of applied research and venture capital, side by side with investors, AI researchers, and engineers building the backbone of our investment intelligence. This is a hands-on role with real stakes. You will be treated as a full member of the team, expected to take a research question from literature to a working prototype and to present your results to the people who make the investment decisions. 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. 1. 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. 2. 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. 3. 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 w

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