This position is available for 18 months with the possibility of an extension. The successful candidate will enjoy an internationally competitive salary and work in a collaborative and creative group in an exclusive research environment.
The candidate will have the primary responsibility to advance new analytical models for predicting the reliability of Power systems, DRAM modules and flash devices that will be applied in the wild. In addition, the candidate is expected to handle the data selection, cleaning and integration tasks prior to the modeling stage.
Requirements
- The ideal candidate is expected to hold a PhD in Computer Science, preferably with an emphasis on machine learning or statistics,
- A strong background in machine learning with a specialization in time and event series analysis, deep learning and potentially survival models,
- Knowledge of reliability of IT components (in particular volatile / non-volatile memory) from a systems perspective is a strong plus,
- An excellent publication track record in top conferences and journals,
- Excellent coding skills in R, Python, and potentially Scala,
- Familiarity with big-data processing frameworks (e.g., Spark stack) would be highly beneficial,
- Familiarity with deep-learning frameworks (e.g., TensorFlow) would be highly beneficial,
The candidate must be self-driven, highly motivated and is required to multitask efficiently.
Diversity
IBM is committed to diversity at the workplace. With us you will find an open, multicultural environment. Excellent flexible working arrangements enable both women and men to strike the desired balance between their professional development and their personal lives.
If you wish to apply, please use this link: https://www.zurich.ibm.com/careers/ and look at the "Post-doctoral researcher: Predictive analytics" posting.