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ML - Research Assistant 

Location Princeton, NJ  
Department Machine Learning 


The Machine Learning Department of NEC Labs America invites applications for Fall and Spring 2019 internships. We have research projects covering many areas of machine learning. The internship will involve research and development of novel machine learning algorithms with applications in image/video analysis, natural language processing, and big data analytics. Our internships normally result in high-quality publications. Minimum duration of the internships are usually 3 months and the exact dates are flexible. Currently, we are looking for interns for projects around video understanding and video analytics systems development.

The Machine Learning group (located at Princeton, NJ) conducts research on various aspects of machine intelligence and reasoning, from the exploration of new algorithms to applications in computer vision and semantic comprehension. Our researchers have extensive expertise in theoretical and application aspects of machine learning, as well as in the development of parallel algorithms for large-scale data analysis.

Ongoing projects focus on video, image and text understanding, QA, deep generative models, robust representation learning, few-shot/zero-shot learning, machine reasoning, interpretable models, data visualization, deep learning systems, and deep reinforcement learning, among others. Publishing is an integral part of our activities as a means for calibrating the quality of the research and to ensure staying at the forefront of technology. In 2018-19, our intern projects have been published in AISTATS, KDD, ICML, CVPR & ICLR.

Application projects emphasize technologies that solve real world problems, and many of our research results have been and will be transferred into industry products.

Position Requirements

• Currently admitted or enrolled in PhD/MSc program in computer science, statistics, electrical engineering, or equivalent.
• Research experience in machine learning, NLP or computer vision.
• Strong computational background.
• Strong programming and scripting skills.
• Strong communication and collaboration skills.


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