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Location ESTEC, Noordwijk, Netherlands Description PLATO Mission and Payload Manager. PLATO is the third medium-sized mission of the European Space Agency’s Cosmic Vision science programme and is
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tumour response to treatment can then bring this much-needed clarity, and implementing this understanding into computational tools can provide the potential for rapid clinical response to patients
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studies independently, working with diverse datasets, developing algorithms and decision rules, and contributing to the refinement of data-driven intervention strategies. Tasks As a postdoctoral researcher
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intelligence and machine learning technologies/algorithms Background in software engineering and programming languages, data analysis and BI tools Proven experience in technical project and service management
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structure, and of the force and tidal field that has been shaping the cosmic web. The basic detection algorithms to infer the overall structure of the cosmic web are the various versions of the scale-space
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Computer Science, Information Science, and Artificial Intelligence and a number of research Master's programmes in these fields. It employs over 200 people, working in four divisions: Algorithms, AI & Data Science
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on the resulting algorithms and pipelines. As an emerging paradigm, differentiable programming builds upon several areas of computer science and applied mathematics, including automatic differentiation, graphical
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Recognition Machine Learning and Pattern Recognition are subareas of AI aimed at the development of algorithms and models capable of learning from data, recognizing patterns, and signal analysis. Tasks include
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algorithms, AI-driven applications and generative AI, exploring how legal mechanisms can prevent and remedy systemic biases that adversely impact LGBTQ+ individuals and which legal routes are available
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for recognition of planetary materials from multispectral datasets. Interns are sought to contribute to the ongoing development of Machine Learning algorithms for recognition of planetary materials from