Postdoc position in Machine Learning applied to fault-detection in Semiconductor fabs

The Data Mining and Machine Learning group (DM2L) at LIRIS laboratory (UMR 5205 CNRS) invites applications for a 1-year Postdoc position in Machine Learning in Lyon.
Starting date: ASAP.
Duration: 1 year.
The successful candidate will develop powerful machine learning algorithms for analyzing sensor data streams (at varying temporal resolution), selecting and extracting features, assessing their relevance and performing both fault detection and fault classification in a supervised or semi-supervised context. The postdoc is funded by a French project called NANO 2017 with STMicroelectronics as main partner. The project aims to enhance semiconductor fabs efficiency by providing methods and tools to better control the process variability, reduce the cycle time and enhance the effectiveness of the production equipment.
Applicants must hold a PhD degree in computer science, electrical engineering or statistics. The successful candidate should have: a strong background in statistics and machine learning methods supported by a solid publication record, excellent programming skills in Python or R, a good proficiency in written english and spoken french.
Some of the things we have to offer: competitive salary, friendly working environment, location near the city center (10 minutes by bicycle) of one Europe's most beautiful and lively cities.
Applications will be reviewed as they arrive, starting immediately, and will be accepted until the position is filled. To apply, e-mail a single PDF file containing your cover letter, curriculum vitae, research statement, list of representative publications with URLs, list of references, with a subject line "Postdoc application: YOUR NAME“.
For further information and informal inquiries, please contact:
Prof. Alexandre AUSSEM
Data Mining & Machine Learning Group (DM2L), http://liris.cnrs.fr/dm2l
Université Claude Bernard Lyon 1, France.
Phone: +33 (0)4 26 23 44 66.
Email: aaussem-AT-univ-lyon1.fr