Internship: Machine Learning

Cambridge, Massachusetts, United States · DA · 1293 expand job description ↓

Description

The Data Analytics Group at MERL is seeking a highly motivated, qualified individual to join our internship program in the summer of 2019. There are multiple opportunities for contributions. Ideal candidates would have a strong background in Generative Models with a particular interest in tractable probabilistic models for continuous variables, approximate DNN-based generative methods (ex. VAE, Boltzman Machines), Reinforcement Learning with experience in an applied setting, classical and deep machine learning methods, or time series analytics. All candidates are expected to have strong programming skills in Python and a good understanding of object-oriented programming and algorithms. Candidates who hold a PhD or in their senior years of a Ph.D. program are encouraged to apply.



Research Areas: Data Analytics

Contact: Emil Laftchiev


Mitsubishi Electric Research Labs, Inc. "MERL" provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability or genetics. In addition to federal law requirements, MERL complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.

MERL expressly prohibits any form of workplace harassment based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. Improper interference with the ability of MERL’s employees to perform their job duties may result in discipline up to and including discharge.

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Are you qualified to apply for an internship at MERL? Qualified applicants for MERL internships are individuals who have or can obtain full authorization to work in the U.S. and do not require export licenses to receive information about the projects they will be exposed to at MERL. The U.S. government prohibits the release of information without an export license to citizens of several countries, including, without limitation, Cuba, Iran, North Korea, Sudan and Syria (Country Group E:1 of Part 740, Supplement 1, of the U.S. Export Administration Regulations).
Have you worked at MERL before?
Are you actively enrolled in a Ph.D. program or are you a Ph.D. degree holder?
Have you published at least one conference or journal manuscript during your Ph.D.? (manuscripts under review can be counted)
Are you comfortable with using Python as your everyday programming language and jupyter notebooks as your as your programming environment?
Are you familiar with algorithms and efficient coding practices?