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Internship

PhD Internship in Anomalib Development

🚀 Off-cycle Internship
💻 Remote

AI generated summary

  • You must be pursuing a PhD in CS, EE, or Math with a focus on ML, CV, and anomaly detection. Proficient in Python, experienced in ML libraries, with strong research, analytical, communication, and collaboration skills.
  • You will conduct advanced research, design and implement anomaly detection algorithms, evaluate performance, collaborate cross-functionally, and contribute scholarly works in visual anomaly detection at Intel Corporation.

Off-cycle Internship

Software Engineering

Description

  • We are offering an internship opportunity for PhD students to join our Anomalib RnD team, focusing on research and development in visual anomaly detection. The intern will play a crucial role in enhancing Anomalib by designing new algorithms and methodologies for detecting anomalies in visual data.

Requirements

  • Education: Currently enrolled in a PhD program in Computer Science, Electrical Engineering, Applied Mathematics, or a related field, with a specific focus on machine learning, computer vision, and anomaly detection.
  • Desired Qualifications:
  • Technical Expertise: Proficient in Python with experience using major machine learning and deep learning libraries (e.g., PyTorch and Lightning). Demonstrated ability in computer vision techniques and anomaly detection methodologies.
  • Research Acumen: Proven track record of research in related areas, evidenced by publications in peer-reviewed journals or presentations at major conferences.
  • Analytical Skills: exceptional problem-solving abilities, capable of working with complex data sets and extracting actionable insights.
  • Communication and Collaboration: Strong written and verbal communication skills, with the ability to effectively document research and collaborate with a multidisciplinary team.

Area of Responsibilities

Software Engineering

Responsibilities

  • Advanced Research: Conduct research to discover and refine novel approaches and techniques in visual anomaly detection. Keep abreast of the latest scientific advancements in machine learning, computer vision, and anomaly detection fields.
  • Algorithm Design and Implementation: Develop and optimize state-of-the-art anomaly detection algorithms that enhance the capabilities of Anomalib. Ensure that these algorithms are efficient, scalable, and integrated seamlessly within the framework.
  • Evaluation and Optimization: Systematically evaluate the performance of developed algorithms using diverse and complex datasets. Utilize feedback from these evaluations to make data-driven improvements.
  • Cross-functional Collaboration: Work closely with both the research and development teams to align research findings with product development goals. Participate in discussions and workshops to share insights and collaboratively solve complex challenges.
  • Scholarly Contribution: Document all phases of research and development comprehensively. Contribute to scientific papers, present findings at conferences, and participate in workshops relevant to the field.

Details

Work type

Full time

Work mode

remote