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Field
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intelligence, and multimodal learning. The main objective of this position is to develop novel generative AI methods for computer vision applications, with a particular focus on Diffusion Models and Vision
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publications in medical image analysis or computer vision video analysis. Knowledge of ultrasound imaging is not a requirement but an interest in research at the interface of machine learning with real-world
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Post-Doctoral Associate in the Center for Interdisciplinary Data Science and Artificial Intelligence
); Relevant research experience in at least one of the following: Social Robotics, human-robot interaction, human-computer interaction, Machine Learning, Affective Computing, Social Signal Processing, Computer
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or computer vision with a video focus, and ideally have prior experience of working with echocardiography or fetal echocardiography or related experience on real-world video analysis Informal enquiries may be
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machine-learning based methods for analyzing IoT time-series data. Your Competencies: We seek a highly motivated researcher with a PhD in computer science, proficiency in software development, and a strong
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neuroscience, and brain-computer interfaces, machine learning and deep learning, statistical modelling, regression methods, and uncertainty quantification, calibration, interlaboratory comparisons, and
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generation, media forensics, anomaly detection, multimodal learning with an emphasis on vision-language models, computer vision applications for space. Key responsabilities: Shape research directions and
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/Resume. Required Education and Experience PhD in Computer Science, Electrical Engineering, Computer Engineering, or a related field. Preferred Qualifications Strong publication record in top-tier AI
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and enthusiastic individual who meets the following criteria: Recently earned a Ph.D. in bioinformatics, computational biology, computer science, electrical and computer engineering, or a related
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or junior graduate students. A formal training, education, or certification in a secondary area (beyond the main PhD focus) such as additive manufacturing, advanced/hybrid manufacturing, machine learning