Ammar Alsheghri
6 months ago
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Postdoctoral Position in Deep Learning for Medical Imaging and Machine Learning with Physics-Based Modeling King Fahd University of Petroleum and Minerals in Saudi Arabia
Degree Level
Postdoc
Field of study
Computer Science
Funding
Full funding availableDeadline
Expired
Country
Saudi Arabia
University
King Fahd University of Petroleum and Minerals

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About this position
A postdoctoral position is available at King Fahd University of Petroleum and Minerals (KFUPM) under the supervision of Professor Ammar Alsheghri. The research focuses on two main areas: deep learning for medical imaging—including classification, segmentation, generation, and regression—and the integration of machine learning with physics-based modeling. This opportunity is ideal for candidates interested in advancing the intersection of artificial intelligence, medical science, and physics.
Applicants must possess a recent Doctoral degree from a reputed university and demonstrate a strong record of ISI-indexed publications. The position offers a competitive salary, housing allowance, medical services, and 30-days paid annual vacation, making it an attractive opportunity for postdoctoral researchers seeking to further their careers in a dynamic and well-supported environment.
Interested candidates should send their CVs to Professor Ammar Alsheghri at [email protected]. Only short-listed candidates will be contacted for further steps. For more information, refer to the LinkedIn profile and post provided in the announcement.
Key research areas include deep learning, medical imaging, machine learning, and physics-based modeling. The position is based in Saudi Arabia at KFUPM, a leading institution in the region for research in artificial intelligence and related fields.
Funding details
Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.
How to apply
Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.
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