Machine Learning Intern - Zebra Technologies

We seek candidates who have the skills and research experience to join a new team to push the boundaries of pure mathematics, theoretical statistics (incl. parametric and non-parametric Bayesian statistics) and machine learning (primarily in deep reinforcement learning). A proven record of publications (at least one first-author paper in reputed conferences such as NeurIPS, COLT, UAI, ICML, AISTATS, JMLR, PAMI, and others) and prototyping skills in terms of developing algorithms, in any language, is critical.

As an industry R&D laboratory, we pursue theoretical and applied research to feed into the other. Like academia, knowledge dissemination is through the publication of papers in reputed journals, conferences and workshops, and patents. We have current collaborations with world-renowned academic institutions; encouraging such industry-academia partnerships is important for research scientists.
Qualifications, skills and other information:

1. Internship applicants will generally study towards a PhD degree in computer science, engineering, statistics, mathematics, and allied disciplines. (core requirement)
2. Knowledge of reinforcement learning (essential) and multi-agent systems (desirable)
3. Knowledge of Bayesian statistics (desirable)
4. Hands-on experience with at least one of the following: Python, C/C++, Java, etc. (core requirement)