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to the Recruitment Coordinator (email: recruitment@maths.ox.ac.uk ), quoting vacancy reference 182497. Applicants will be selected for interview purely based on their ability to satisfy the selection criteria as
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: Please email applications to Dr. Anusha Kalbasi (akalbasi@stanford.edu (link sends e-mail) ). Does this position pay above the required minimum?: No. The expected base pay for this position is the Stanford
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Max Planck Institute for Dynamics and Self-Organization, Göttingen | Gottingen, Niedersachsen | Germany | 8 days ago
research team. The ideal candidate should have: a PhD/DPhil degree (or comparable) with a background in theoretical physics, applied mathematics or related disciplines from a recognized university, prior
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, or be close to completing, a PhD in mathematics or a related discipline, and possess sufficient specialist knowledge in either random matrix theory, analytic number theory or probability to work within
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Mississippi. Apply computer vision and machine learning approaches to integrate ground-based imagery, remote sensing data, and lidar data for high-resolution flood detection and mapping. Develop and calibrate
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learning, transfer learning, foundation models, and self-supervised learning. Experience in dealing with large medical datasets (e.g., electronic health records data or medical images) Ability to use high
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computer vision/machine learning or remote sensing. Experience working as part of an interdisciplinary research team. Have a license to operate a motor vehicle in the United States or the ability to obtain
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computing. You will join the Vision & Human-Robot Interaction (VHR) Group, which brings together researchers working at the intersection of computer vision, robotics, and assistive technologies. The team is
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(cover letter) CV Academic Diplomas (MSc/PhD – in English) List of publications Applications received after the deadline will not be considered. All interested candidates irrespective of age, gender
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and interpersonal skills. Skills & Experience (specific to the project): PhD in Computer Science, Software Engineering, Electronic Engineering, with an appropriate specialism (e.g. Creative Coding