Internship: Implicit Neural Networks for Object Representation Reconstruction
Mitsubishi Electric Research Labs, United States
Job Description
MERL is looking for a highly motivated intern to work on an original research project in 3D representation and reconstruction using implicit neural networks. A strong background in 3D computer vision is required. Experience in deep learning will be valued. The successful candidate is expected to have published or submitted at least one paper in a top-tier computer vision venue, such as CVPR, ECCV, ICCV, NeurIPS, ICLR, and ICML, along with solid programming skills in Python and/or C++. The position is available for graduate students on a Ph.D. track. Duration and start dates are flexible.
Research Areas: Computer Vision
Contact: Pedro Miraldo
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.
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Working at MERL requires full authorization to work in the U.S and access to technology, software and other information that is subject to governmental access control restrictions, due to export controls. Employment is conditioned on continued full authorization to work in the U.S and the availability of government authorization for the release of these items, which might include without limitation, obtaining an export license or other documentation. MERL may delay commencement of employment, rescind an offer of employment, terminate employment, and/or modify job responsibilities, compensation, benefits, and/or access to MERL facilities and information systems, as MERL deems appropriate, to ensure practical compliance with applicable employment law and government access control restrictions.