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embodied and justice-oriented approaches to datafication literacy, to support human agency and mitigate algorithmic harms. The focus will be on empirical research that uses different design and game-making
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applications. Possess system analytical and algorithmic thinking Demonstrate a curious and collaborative mindset, strong research motivation, and eagerness to apply your skills to diverse computational
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developed by the project partners will be based on two key technologies: machine learning algorithms that generate artificial yet realistic data points (synthetic health data) and secure multi-party
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will design and implement novel computer vision and machine learning methods for “sensorized” cameras that extract medically relevant features without transmitting raw video. You will evaluate algorithms
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such as earth with different sizes of rocks. 2) Development of advanced control algorithms integrated with force and loss models to prevent overloads and hazardous situations, ensuring operational
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that are of practical interest. The postdoctoral researcher will contribute to the theoretical foundations of inverse problems involving wave phenomena, develop cutting-edge computational algorithms, and apply
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: neuromorphic algorithms, machine learning, classifier development, AI programming Key tasks include experimental and/or computational research, collaboration within the project team, publishing results in high
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, PyTorch, Keras, scikit-learn) and strong understanding of machine learning algorithms, deep learning architectures, and statistical methods Good skills in extraction of data from structured/unstructured
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experimental materials synthesis, characterisation or both, and optionally, with experience developing algorithms for accelerated discovery based on data collection from automated instruments. Practical
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skills in programming, signal analysis and algorithms. Excellent/good skills in spoken and written English. Advantages Ability to work independently, formulate and solve research problems, and communicate