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University. Requirements A master’s degree in (applied) mathematics (or related), with a strong background in computational methods, preferably also using computational frameworks for machine learning in
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for a four-year assignment. During this time, you will be actively working and learning on the job and will benefit from valuable mobility and developmental opportunities that will prepare you for a
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well as stimulating the use of campaign data in new EO domains (such as big data analytics, artificial intelligence and machine learning); initiating and conducting in-house and external scientific studies to support
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develop a simplified model focusing on the leader stage. You will: Analyze experimental data and microscopic simulations Identify relevant physical features and parameters Apply machine learning techniques
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technologies, for example, using machine learning techniques to support long term exploration; Topics related to ‘off world living’, e.g. human factors, design and concept illustration; Crew Health and
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technologies, for example, using machine learning techniques to support long term exploration; Topics related to ‘off world living’, e.g. human factors, design and concept illustration; Crew Health and
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Advanced control, optimisation and estimation techniques Artificial intelligence and machine learning techniques for AOCS applications and engineering AOCS modelling, AOCS software, AOCS hardware and
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-up; Perform the tests according to the test plan; Data analysis and reporting. In this project you will learn about space science instruments, space science detector technology, performance characterization
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methodologies, such as additive manufacturing, for projects within the centre and for space exploration; Developing new ideas around medical technologies, for example, using machine learning techniques to support