Join Prior Labs!

Prior Labs is building breakthrough foundation models that understand spreadsheets and databases - the backbone of science and business. Foundation models have transformed text and images, but structured data has remained largely untouched. We're tackling this $100B+ opportunity to revolutionize how we approach scientific discovery, medical research, financial modeling, and business intelligence.

We aim to be the world leading organization working on structured data. Our TabPFN v2 model, was just published in the Nature Journal and is the new state-of-the-art for small structured data. Our models have significant traction (900K+ downloads, 2,000+ GitHub stars) and we are now building the next generation of models that combine AI advances with specialized architectures for structured data.

With backing from top-tier investors and some of the top AI leaders, we're rapidly moving toward commercialization. Want to help organizations worldwide unlock the true value of their most critical data assets? Join us in making it happen.

Core Areas of Impact

You'll be among the first scientists collaborating and working on an entirely new class of AI models, not just incremental improvements. As an early-stage startup working on foundation models for tabular data, we have countless exciting research ideas and problems to explore - you're sure to find challenges that match your interests and expertise. We are tackling challenges like:

Researching causal understanding in foundation models to predict the effects of interventions
Developing methods for causal inference and causal discovery
Designing models capable of understanding and simulating causal relationships in complex datasets

What We're Looking For

Currently pursuing or holding a PhD in Computer Science, Applied Mathematics, Statistics, Electrical Engineering, or a related field (we will also consider exceptional Master's students)
Demonstrated research experience in causality, including causal inference, causal discovery, and intervention prediction
Deep experience with ML frameworks, especially PyTorch and scikit-learn
Strong engineering fundamentals with excellent Python expertise
Experience in data-science and working with tabular data or time series
Publications at top-tier venues (NeurIPS, ICML, ICLR) or significant open-source contributions

Benefits

Strong mentorship and professional development opportunities
Work with state-of-the-art ML architecture and substantial compute resources
Shape the future of data science and AI

Location & Work Style

Headquartered in Freiburg, Germany - a university city at the edge of the Black Forest, Switzerland and France and office in Berlin
Opening London in 2025

We're building a team that combines technical excellence with our core principles:

High-performing empathy - We deliver exceptional results while supporting and respecting each other
Undogmatic problem-solving - We value practical solutions over rigid principles
Positive impact - We integrate ethical considerations into everything we build
Product driven - We're driven to create breakthrough tools that transform how people work with data

We're at the forefront of bringing foundation model breakthroughs to tabular data, with the potential to transform how organizations worldwide make decisions. If you're excited about creating robust, scalable systems that will power the next generation of AI applications, we'd love to hear from you.

Prior Labs

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Research Scientist Intern, Causality (PhD)