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Field
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: PhD degree in Computer Science, Electrical Engineering, or a closely related field Strong research background in computer vision and deep learning Solid experience with multimodal learning, segmentation
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computational models of vision and machine learning methods (for example CNNs, deep generative models, encoding models) is preferred but not required Ability to communicate scientific results clearly through
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biology, statistics, computer science, or a closely related field). Degree must have been received within the past four years. Preferred skills: Computer skills Knowledge and understanding of genome
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machine learning, computer vision, and medical image analysis, with publications in top-tier AI and medical image analysis conferences and journals, including CVPR, ICCV, ECCV, NeurIPS, MICCAI, TPAMI, TIP
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advantageous. Additional preference will be given to candidates with computational experience in protein structure–function prediction, metabolic or biochemical pathway analysis, machine learning applications in
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. Develop skills in coupling crop and hydrology models at watershed scales. Gain experience validating models using large, multi-source datasets. Learn to apply high-performance computing and machine learning
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Language Models (MLLMs) and their agentic implementations. Develop and benchmark novel adversarial attacks and defense strategies, focusing on the intersection of computer vision, natural language processing
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society and realising our vision of making the world a better place. We are delighted to announce exciting new opportunities to join our community. EMBRACE is a visionary, multicomponent international
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deployment, and leadership skills. Function 3 Postdoctoral researchers are expected to: Lead research projects within one of the focus areas above. Publish in leading robotics, computer vision, and machine
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that research delivers against their requirements. Qualifications: APhD in Computer Science/Computer Vision/AI or a closely related field. Extensive research experiencein machine learning, deep learning, and self