Internship - Multimodal Algorithmic Reasoning

Mitsubishi Electric Research Laboratories; Cambridge (MA); On-site; USD 27,552 - 55,104; Part time

Job summary

A leading research organization in Cambridge is seeking an intern for a role focused on multimodal algorithmic reasoning. The ideal candidate is a PhD student with experience in machine learning and computer vision, specifically in training multimodal models for vision-and-language tasks. This position offers an opportunity to collaborate with the computer vision team, and candidates are encouraged to bring a strong publication record and experience in mathematical reasoning. Strong programming skills in Python using PyTorch are required.

Qualifications

• Strong background in machine learning and computer vision.
• Prior experience with training multimodal LLMs for vision-and-language tasks.
• Experience in participating and winning mathematical Olympiads.

Responsibilities

• Research on multimodal large language models and neural algorithmic reasoning.
• Collaborate with researchers in the computer vision team.
• Develop algorithms and prepare manuscripts for publications.

Skills

Experience with training large vision-and-language models

Experience with solving mathematical reasoning problems

Programming in Python using PyTorch

Strong track record of publications

Education

Enrolled in a PhD program

Job description

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Internship - Multimodal Algorithmic Reasoning

MERL is looking for a self-motivated intern to research on problems at the intersection of multimodal large language models and neural algorithmic reasoning. An ideal intern would be a Ph.D. student with a strong background in machine learning and computer vision. The candidate must have prior experience with training multimodal LLMs for solving vision-and-language tasks. Experience in participating and winning mathematical Olympiads is desired. Publications in theoretical machine learning venues would be a strong plus. The intern is expected to collaborate with researchers in the computer vision team at MERL to develop algorithms and prepare manuscripts for scientific publications.

Required Specific Experience

• Experience with training large vision-and-language models
• Experience with solving mathematical reasoning problems
• Experience with programming in Python using PyTorch
• Enrolled in a PhD program
• Strong track record of publications in top-tier computer vision and machine learning venues (such as CVPR, NeurIPS, etc.).

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.

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.