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corrosion detection in metallic structures. The position focuses on the development, training and validation of artificial intelligence algorithms for multispectral image processing, with the objective
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combination of education and relevant work experience to equal at least nine years Strong foundation in algorithms, data structures, software engineering principles, and computational methods. Strong
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the correctness, robustness and reliability of deep neural networks and AI-enabled software systems. Job Responsibilities: Develop novel methods and algorithms for the verification, testing and robustness analysis
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machine learning techniques to raw ultrasound data. The project involves developing novel algorithms that integrate physics, engineering, and AI to extract meaningful and clinically relevant information
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to accurate sample reconstructions using advanced signal processing and tomographic reconstruction algorithms. With the inclusion of noise the object estimation accuracy will be based on statistical concepts
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analytical tasks, which have the clinical value in the real-world employment. • To develop novel models and algorithms for 2D or 3D medical vision tasks, such as surgical scene segmentation, depth
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on the review, and present them to senior staff. Contributing to prototyping and developing machine learning algorithms specifically designed for medical imaging applications. In addition, performs analysis
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inference) Algorithmic development for bilevel (or multilevel) optimization Methodological developments in Bayesian statistics and/or decision analysis Application of adversarial risk analysis within security
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, implementation, and evaluation ● AI in public management, government operations, and public service delivery ● Algorithmic decision making, accountability, and transparency ● The responsible and ethical use of AI
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reconfiguration operation. Develop and evaluate fast and efficient scheduling algorithms for fast control and reconfiguration of the optical AI compute clusters. Realize a small-scale compute cluster lab testbed