Overview In this role, you will advance foundational ML research with a focus on sampling and generative modeling to address biological questions. You'll contribute to open science through publications and by presenting at scientific venues. You will collaborate with a large, globally distributed team to push the state of the art and to shape experiments and reusable code. This position sits within Roche's Computational Sciences Center of Excellence, accelerating data-driven discovery for patients worldwide. A strong research impact and cross-functional collaboration are central to this opportunity.
Compensation / Benefits- discretionary annual bonus
Responsibilities- Develop theoretical frameworks and algorithms for sampling and generative modeling
- Contribute to publications and present results at internal and external conferences
- Collaborate and execute on research that advances state-of-the-art in ML
- Directly contribute to experiments: design, code, run evaluations, organize results
- Work with a large, globally distributed team
Key requirements- PhD in Mathematics, Physics, Computer Science, Statistics, Machine Learning, or related disciplines with 2-7 years of experience
- Strong publication record in generative modeling (JMLR, NeurIPS/ICML/ICLR/COLT)
- Strong communication and collaboration skills
- Preferred: published work with theoretical contributions
- strong communication
- collaboration
- ability to work in a distributed team
- generative modeling
- theoretical ML
- sampling methods
