Research Scientist Intern (PhD)

WHO WE ARE Foundation models transformed text and images. Structured data - the largest and most consequential data format in the world - stayed untouched, until now. What LLMs did for language, we're doing for tables. We pioneered tabular foundation models: TabPFN v2 was a Nature https://www.nature.com/articles/s41586-024-08328-6 cover story, has passed 3.5M+ downloads and 7,500+ GitHub stars, and runs in production from detecting lung disease with Oxford Cancer Analytics https://www.oxcan.org/news/prior-labs-and-oxford-cancer-analytics-partner-to-advance-liquid-biopsy-and-clinical-decision-making-in-lung-disease to preventing train failures with Hitachi https://siliconangle.com/2025/12/01/prior-labs-debuts-tabular-ai-foundation-model-scales-10-million-rows/. The hardest problems - millions of rows, real-time inference, entirely new modalities - are still open, and no one else is working on them at this level. We're a small, highly selective team of 40+ https://priorlabs.ai/about with backgrounds from Google, DeepMind, Meta, Apple, Amazon, Jane Street, and CERN, led by Frank Hutter https://www.linkedin.com/in/frank-hutter-9190b24b/, Noah Hollmann https://www.linkedin.com/in/noah-hollmann-668b9010b/, and Sauraj Gambhir https://www.linkedin.com/in/sauraj-g/, and advised by Bernhard Schölkopf and Turing Award winner Yann LeCun. In July 2026, less than 18 months after our €9M pre-seed, we joined SAP https://priorlabs.ai/blog-posts/priorlabs-sap as an independent frontier AI lab - same team, mission, and open-weights models, now backed by more than €1 billion over four years. ABOUT THE ROLE You'll join the research team and work hands-on on an entirely new class of AI models. We have more open research problems than people to work on them, so you'll find challenges that match your interests and expertise. Problems we're working on: - Scaling our transformer architectures from 10K to 1M+ samples while maintaining performance - Building multimodal models that combine text and tabular understanding on proprietary data - Developing specialized architectures for time series, forecasting, and anomaly detection - Creating efficient inference methods for production deployment - Researching causal understanding in foundation models - Designing novel approaches for handling multiple related tables 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) - 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 architectures, substantial compute resources, and a world-class team - Comprehensive benefits including healthcare, transportation, and fitness LIFE AT PRIOR LABS You'll work alongside researchers and builders who hold themselves to a very high bar - in the quality of their work and in how they work with each other. We move fast and still take the time to do things right. Our teams are based in Berlin, Freiburg, and New York - when you're working on something as hard as TabPFN, being in the same room matters. But great people come from everywhere, and in exceptional cases we're open to remote, which usually means frequent travel to one of our offices. Wherever you're based, the whole company comes together regularly for offsites to build and celebrate together. OUR COMMITMENTS The best products and teams are built by people with a wide range of perspectives and backgrounds. We welcome applications from all identities and walks of life - especially if you've ever felt discouraged by "not checking every box" - and provide equal oppor…