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Field
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Kahl (Computer Vision, Chalmers), Kathlén Kohn (Algebraic Geometry, KTH), and Mårten Björkman (Robotics, Perception and Learning, KTH). The research focuses on developing novel machine learning methods
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Job Description We offer an exciting postdoc position dedicated to developing methods for detecting performance disparities in foundation models for fetal ultrasound and understanding what causes
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combine large-scale data, computational methods, and clearly articulated social-science theories to improve our understanding of society. Recent advances in machine learning, natural language processing
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, use of microscopes, data acquisition, inverse problems in imaging, optimization methods and image estimation and in particular knowledge in methods for super resolution structured illumination
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Knowledge of and experience in general analytical methods development and good analytical practices Maintains a working knowledge of significant developments and trends in the field SKILLS Outstanding
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reduction and uncertainty quantification for biological flows. The goal of the project is, in particular, the development of robust methods to quantify the propagation of domain uncertainties in
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Christmas Eve when it falls on a weekday) for all full time staff. Use our total rewards calculator: https://www.hw.ac.uk/about/work/total-rewards-calculator.htm to see the value of benefits provided by
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TPMS data, high-speed wheel encoders, CAN data, accelerometer data, and acoustics data. In addition to other cloud-based data for weather-friction estimates and crowdsourced vehicle data for estimating