Industrial Inspection: Anomaly Localization Internship

Mitsubishi Electric Research Laboratories, Inc.; Cambridge (MA); On-site; USD 67,000 - 89,000; Full time

Benefits offered by this job

Relocation stipend

Travel coverage

Charlie Card for local commuting

Job summary

MERL invites a self-motivated intern to advance anomaly localization for industrial inspection using computer vision. The work includes few/zero/any-shot anomaly detection and integrating large foundation models.

A PhD student with publications in CV/ML is preferred; you will collaborate with MERL researchers to develop algorithms and manuscripts. Internship duration is at least 3 months with a flexible start date.

Qualifications

• Proficiency in Python programming and familiarity with at least one deep learning framework.
• Experience with PyTorch and large foundation models (e.g. CLIP, Gemma, Qwen).
• PhD candidate with publications in top CV/ML venues preferred.

Responsibilities

• Collaborate with MERL researchers to develop anomaly localization algorithms.
• Prepare manuscripts for scientific publications.
• Contribute to industrial inspection datasets and evaluation protocols.

Skills

Python

PyTorch

Foundation models

Education

PhD student

Tools

GPT/LLM frameworks

Job description

MERL invites a self-motivated intern to advance anomaly localization for industrial inspection using computer vision. The work includes few/zero/any-shot anomaly detection and integrating large foundation models.

A PhD student with publications in CV/ML is preferred; you will collaborate with MERL researchers to develop algorithms and manuscripts. Internship duration is at least 3 months with a flexible start date.