Lam Research

Job Responsibilities :

You will be working with multi-dimensional datasets from various time-series sensors to develop generative and discriminative models. Your portfolio includes deploying deep learning methods with traditional computer vision to build robust image detection and feature recognition models, designing advanced deep learning (LSTM, RNN) for advanced process control, writing robust and maintainable code that is well documentation with version control in Python/R, identifying core requirements for image segmentation and creating and deploying apps while providing UX feedback.



Job Requirements

Masters or PhD in Data Science, Computer Science, Electrical Engineering, Physics, Materials Science or related field.
At least one year of experience with applied computer vision and machine learning algorithms for a Masters Candidate or extensive thesis work in these areas.
Solid mathematics background (linear algebra, probability, optimization).
Knowledge in deep learning architectures for computer vision, and associated libraries and frameworks (Spark, Keras, Tensorflow, OpenCV, Skimage, etc.).
Experience with and implementing CNN’s, feature detection, and classification.
Experience with solr, and SQL or HDFS/HBase is a plus.
At least three years of experience within the semiconductor or related field is preferred.
Previous work analyzing multi-dimensional data, including segmentation, reconstruction, classification, or manipulation is a big plus
Strong communication skills.

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