Post-doctoral researcher and Research Staff Member

Machine learning algorithms & theory

Ref. 2019_051

Project description

The Cloud Storage and Analytics team at IBM Research – Zurich is conducting state-of-the-art research related to algorithms and systems for large-scale machine learning. We are looking to expand our team by creating new positions focused on theory and algorithms for machine learning. These positions will involve designing and prototyping of new machine learning algorithms and evaluating their performance both empirically and theoretically. Topics of interest include (but are not limited to) ensemble learning, distributed learning, boosting and automated machine learning.

Successful research will be published at top AI conferences and potentially integrated into IBM’s AI product offerings. Our team has a proven track record in this area, having developed a new software framework for high-performance, distributed machine learning (Snap ML), and published research papers at top AI conferences. We are seeking outstanding researchers (permanent and post-doctoral positions) to contribute to the above research project.


Candidates are expected to have the following background and interests

  • PhD in Computer Science, Applied Mathematics, Statistics or a related field
  • Publications at top AI conferences (NeurIPS, ICML, AISTATS, AAAI)
  • Experience with C++ and/or Python
  • Practical experience with machine-learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch)
  • Familiarity with version control systems (git)
  • Self-motivation and a passion for problem solving
  • Excellent teamwork as well as written and oral communication skills

The positions are available immediately (post-doctoral positions for a duration of 24 months). The successful candidates will enjoy an internationally competitive salary and work in a collaborative and creative group in an exclusive research environment.


IBM is committed to diversity at the workplace. With us you will find an open, multicultural environment. We offer a diverse, independent professional activity, with experienced colleagues in a friendly atmosphere on our campus. You will find a dynamic, multi-cultural environment, and flexible working conditions. Women are expressly invited to apply.

How to apply

Candidates with the background and interests listed above are encouraged to send their CV including a list of publications and references.