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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


  • 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.


  • 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


  • 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.


Work type

Full time

Work mode