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described in the project overview. Owing to the current composition of the project team, there will be a mild preference for candidates opting for project 2 on “Models and machine learning”. An explanation
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, which has multiple test machines with GPUs and AI accelerators. The algorithms used can be bound by the available compute power or memory bandwidth in different parts of the program. This information will
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for systematic reviews, Mendeley for citation management and SPSS for data/statistical analysis/machine learning. Diversity, Equity and Inclusiveness ESA is an equal opportunity employer, committed to achieving
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and strong preference for also excellent Dutch language skills. You’re able to adapt and learn quickly, you like to turn your ideas into action and are able to work independently. Strong detail
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business card) Discount on membership of Erasmus Sport. Access to online learning platform GoodHabitz and wellbeing platform OpenUp. Regular fun work events and drinks. Participation in our collective
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records from satellite data, and/or improved methods of uncertainty characterisation, including the use of artificial intelligence and machine learning to improve or analyse satellite climate data records
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in combination with other machine learning techniques, to create predictive models. You will engage in an interactive feedback loop with domain experts to analyze discovered models and remove any
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Machine Learning Problems > Constantly questions finance/trading data and stays motivated to seek answers despite most often proving that there is no correlation or signal > Experience in setup of research
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networks, or network science, and relevant background knowledge n methods in machine learning and AI. The successful candidate will focus on innovating the field of network analysis with AI methods. Examples
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performance in accordance with the respective service level and application of internal processes. This includes contributing to risk management definition, mitigation actions and lessons learned exercises