Internship openings in audio, speech, and language at MERL, Cambridge, MA

[Jonathan Le Roux]

MERL (Mitsubishi Electric Research Labs) has multiple openings throughout 2019 in areas related to audio, speech, and language, detailed below. The interns will collaborate tightly with MERL researchers to derive and implement new models and optimization methods, conduct experiments, and prepare results for high impact publication. The duration of each internship is expected to be 3-6 months.

MERL is an amazing place for internships. Our interns have a unique opportunity to be involved in cutting-edge research towards publication in top-tier venues, and interact with a number of their peers from around the world with a large variety of interests. We also have a great social program.

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SA1132: End-to-end acoustic analysis recognition and inference
MERL is looking for an intern to work on fundamental research in the area of end-to-end acoustic analysis, recognition, and inference using machine learning techniques such as deep learning. The ideal candidate would be a senior Ph.D. student with experience in one or more of source separation, speech recognition, and natural language processing including practical machine learning algorithms with related programming skills.

Apply: https://merl.workable.com/jobs/605941/candidates/new
Host: Takaaki Hori (http://www.merl.com/people/thori)

SA1245: Source Separation
We are seeking graduate students interested in helping advance the field of source separation and speech enhancement in extreme environments using the latest developments in deep learning. The ideal candidate would be a senior Ph.D. student with experience in audio signal processing, speech modeling, probabilistic modeling, and deep learning.

Apply: https://merl.workable.com/jobs/849198/candidates/new
Host: Gordon Wichern (http://www.merl.com/people/wichern)

SA1246: Audio Visual Semantic Understanding
MERL is looking for an intern to work on fundamental research in the area of audiovisual semantic understanding for scene-aware dialog technologies by combining end-to-end dialog and video scene understanding technologies. The ideal candidate would be a senior Ph.D. student with experience in one or more of video captioning/description, end-to-end conversation modeling and natural language processing including practical machine learning algorithms with related programming skills.

Apply: https://merl.workable.com/jobs/849196/candidates/new
Host: Chiori Hori (http://www.merl.com/people/chori)