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Full Time, Fixed Term (31/07/2028) The closing date for applications is 23.59 on 10 October 2025 Interview Date : 20 October 2025 By reference to the applicable SOC code for this role, sponsorship
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experimentalists and adapt code for real-world data. Preferred Knowledge, Skills, and Abilities: Familiarity with compressed sensing and/or convex optimization (e.g., total variation minimization). Expertise in
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adapt code for real-world data. Preferred Knowledge, Skills, and Abilities: Familiarity with compressed sensing and/or convex optimization (e.g., total variation minimization). Expertise in Python
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 days ago
. Responsibilities for this position includes:* Developing deep-learning approaches for insight and analysis about mouse behavior from video * Machine Learning: use your expertise in statistics and machine learning
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qualified in relevant subject area (or nearing completion) Good knowledge of computer vision algorithms for image and video processing Strong experience in machine learning or deep learning for medical image
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strategies are integrated into the project (e.g., video blogs and academic workshops) and the post holder will be expected to support these activities. You will have: a PhD in cardiovascular or a related field
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collaborative environment. Unable to show this video due to your cookie preferences
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future colleagues? You can watch these videos: Aalto University – Towards a better world , Aalto People , and Shaping a Sustainable Future . For more information about living in Finland: https
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experience developing and adapting qualitative coding schemes based on dialogue and behaviors (from video, audio, eye movements, and log file data), as well as experience working with physiological sensors
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/Temporary Regular Job Code 9546 Employee Class Acad Prof and Admin Add to My Favorite Jobs Email this Job About the Job We are looking for a quantitative wildlife ecologist to join our team to study how