22 coding-"https:"-"FEMTO-ST"-"CSIC"-"P"-"UCL" "https:" "https:" "https:" "https:" "https:" "UNIV" positions at Lancaster University in United Kingdom
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approach for detecting sparse, unlabelled events in noisy multivariate time-series • Why this project appeals to you now Code sample (optional): GitHub repo/notebook demonstrating your implementation
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and oversee code reviews across all code platforms, ensuring that security considerations are thoroughly evaluated and best practices are consistently applied Act as a subject matter expert and point
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