✨ AI Summary
Khalifa University is seeking a Postdoctoral Fellow for their Medical Imaging department in Abu Dhabi. This full-time, permanent position involves conducting experiments, developing adaptive curriculum learning approaches for multi-modal medical imaging models, and contributing to publications. The ideal candidate must have a PhD from a top-ranked university and experience in AI model training, computer programming, and relevant academic publishing. Familiarity with multi-modality, natural language processing, machine learning, deep learning, and computer vision is preferred.
Requirements
The postdoctoral fellow will be responsible for running different experiments under the guidance and supervision of the principal investigator (PI). The fellow will be involved in all experimental aspects of the project. The fellow will help create, investigate, and test different modality-aware adaptive curriculum learning approaches for multi-modal medical imaging models that consider the innate nature of real-world medical data. Running experiments (including identifying and preparing data for training, training AI models, and thoroughly testing AI models)Reporting and discussing results and work weekly with the PIDrafting papers and publications containing the results of experiments alongside the PIDedicate 100% of work time to this projectPhD gained from and/or experience working in a top 200 QS or THE ranked UniversityRelevant academic publishing experienceExperience with training and running AI modelsExperience with multi-modality or natural language processingPossessing machine learning, deep learning, and computer vision (CV) foundationsExperience with computer programming.
Description
The postdoctoral fellow will be responsible for running different experiments under the guidance and supervision of the principal investigator (PI). The fellow will be involved in all experimental aspects of the project. The fellow will help create, investigate, and test different modality-aware adaptive curriculum learning approaches for multi-modal medical imaging models that consider the innate nature of real-world medical data. Running experiments (including identifying and preparing data for training, training AI models, and thoroughly testing AI models)Reporting and discussing results and work weekly with the PIDrafting papers and publications containing the results of experiments alongside the PIDedicate 100% of work time to this projectPhD gained from and/or experience working in a top 200 QS or THE ranked UniversityRelevant academic publishing experienceExperience with training and running AI modelsExperience with multi-modality or natural language processingPossessing machine learning, deep learning, and computer vision (CV) foundationsExperience with computer programming