Internship: Anomaly Detection in Time Series
MERL is looking for a highly motivated intern to work on developing anomaly detection algorithms for time series analysis. Successful candidate will collaborate with MERL researchers to design, analyze, and implement new algorithms, conduct experiments, and prepare results for publication. The ideal candidate is expected to have a strong background in time series analytics with experience in algorithms for time-series representation, subsequence matching, pattern matching and time-series clustering. The candidate is expected to have strong programming skills in C++ and Python. Candidates who hold a PhD or in their senior years of a Ph.D. program in Electrical Engineering, Computer Science, Statistics or a related field are encouraged to apply. Interested candidates are encouraged to apply with their full CV with list of related publications and links to github code repositories (if any). [The duration of the internship is 12 weeks.] The position is available starting September 2017.
Research Area: Data Analytics
Contact: Devesh Jha
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