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as healthcare, cyber-physical systems, and foundation models, including large language models. Depending on the candidate’s interests and background, the project can focus on algorithm design
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Liège. Your tasks in detail: Develop an event-driven learning algorithm for latent reasoning that sparsely updates network state and parameters in complex reasoning scenarios. Explore hardware
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not mandatory. Specific Technical Requirements: Proficiency in one or more programming languages, such as Python, MATLAB, C/C++, or Java, with a strong emphasis on scientific computing and algorithm
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quantification. Your task in detail: Design a data pipeline to extract and preprocess activity-relevant features from monitored building power consumption data Develop a classification algorithm (e.g
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possibility to expand the existing lab-setup with multispectral sensing capabilities. A selected Gaussian Splatting algorithm (e.g. RefGS, 3DGSDR, or GShader) can serve as a starting point for
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from sparse phase-contrast CT acquisitions of oncological specimens Comparison with standard histology and assessment of algorithm performance Present results at international conferences as well as
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Required skills/knowledge includes: Data science/algorithm development Data science / Machine Learning languages to include Python Research, development and implementation of machine learning models
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optimization Experience with large-scale algorithm design and implementation Knowledge of decision making under uncertainty Ideally, some exposure to machine learning methods A passion for research
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: Data science/algorithm development Data science / Machine Learning languages to include Python Research, development and implementation of machine learning models Preferred skills/knowledge includes
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digital, data- and algorithm-driven world. Integreat develops theories, methods, models, and algorithms that integrate general and domain-specific knowledge with data, laying the foundations of next