Real-Time Computer Vision Scientist for Infrared Imaging

Karlstad University; Thuwal; On-site; SAR 180,000 - 300,000; Full time

Benefits offered by this job

Competitive salary

Interdisciplinary collaboration

Job summary

KAUST invites applications for a Postdoctoral Researcher or Research Scientist in Computer Vision & AI for Infrared Imaging. The role centers on developing AI-driven analytics for real-time monitoring, with emphasis on anomaly detection in solar panels and battery systems.

Candidates should have a PhD (or MSc/PhD) in a related field, strong CV/DL expertise, Python proficiency, and a track record of deployable models. Open date 2026-04-08; application deadline 2026-10-08.

Qualifications

• PhD (Postdoc) or MSc/PhD (Research Scientist) in Computer Science, Electrical Engineering, Applied Mathematics, or a related field.
• Strong expertise in computer vision and image processing; deep learning (e.g., PyTorch, TensorFlow); data-driven modeling and analysis.
• Proficiency in Python and standard ML libraries.
• Demonstrated ability to develop practical, deployable models.

Responsibilities

• Develop computer vision and deep learning algorithms for image-based detection.
• Implement data fusion and image analysis pipelines for scientific/engineering applications.
• Build scalable and real-time inference workflows.
• Collaborate with multidisciplinary teams (materials, devices, and systems).
• Contribute to publications, reports, and student supervision.
• Postdoctoral Researcher or Research Scientist (depending on experience)
• Competitive salary and research environment
• Based at KAUST with interdisciplinary collaboration

Skills

Computer vision

Deep learning

Python

Image processing

Education

PhD (Postdoc)

MSc/PhD (Research Scientist)

Tools

PyTorch

TensorFlow

Job description

KAUST invites applications for a Postdoctoral Researcher or Research Scientist in Computer Vision & AI for Infrared Imaging. The role centers on developing AI-driven analytics for real-time monitoring, with emphasis on anomaly detection in solar panels and battery systems.

Candidates should have a PhD (or MSc/PhD) in a related field, strong CV/DL expertise, Python proficiency, and a track record of deployable models. Open date 2026-04-08; application deadline 2026-10-08.