We are seeking a graduate student interested in helping advance the fields of source separation, speech enhancement, and sound event detection/localization in challenging multi-source and far-field scenarios. The intern will collaborate with MERL researchers to derive and implement new models and optimization methods, conduct experiments, and prepare results for publication. The ideal candidate would be a senior Ph.D. student with experience in audio signal processing, microphone array processing, probabilistic modeling, and deep learning techniques requiring minimal supervision (e.g., unsupervised, weakly-supervised, self-supervised, or few shot learning). The internship will take place during fall/winter 2021 with an expected duration of 3-6 months and a flexible start date. This internship is preferred to be onsite at MERL, but may be done remotely where you live if the COVID pandemic makes it necessary.

MERL is seeking an intern to work on research for quantum machine learning (QML). The ideal candidate is an experienced PhD student or post-graduate researcher having an excellent background in quantum computing, deep learning, and signal processing. Proficient programming skills with PyTorch, Qiskit, and PennyLane will be additional assets to this position. Also note that we wish to fill this position as soon as possible and expect that the candidate will be available during this fall/winter. This internship is preferred to be onsite at MERL, but may be done remotely where you live if the COVID pandemic makes it necessary.

MERL is seeking a motivated and qualified individual to conduct research in control of electrical machines. The ideal candidate should have solid backgrounds in adaptive dynamic programming and state/parameter estimation for electrical machines, demonstrated capability to publish results in leading conferences/journals, and experience with real-time control experiments involving high power devices. Senior Ph.D. students are encouraged to apply. Start date for this internship is flexible and the duration is about 3 months.