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Field
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achieve automated data driven optimization (in terms of time and quality) of polishing process parameters by application of machine learning algorithms, leading to a robust, repeatable and fast polishing
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data is lacking. With the DataLibra project, we aim to close this gap, by developing AI models and tools for structured data (Table Representation Learning), to help organizations, of any size, domain
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, memristive devices), and the evaluation with e.g. machine learning and image processing benchmarks Requirements: excellent university degree (master or comparable) in computer engineering or electrical
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, quantitative or mixed-methods); Independent thinking and critical analytical skills; Good collaboration skills and an ability to join interdisciplinary and intercultural academic communities; Excellent oral and
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health monitoring, supporting studies in military aircraft systems. Engaging with these facilities allows students to acquire practical skills and technical expertise, enhancing their research capabilities
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for research into thermal management and system health monitoring, supporting studies in military aircraft systems. Engaging with these facilities allows students to acquire practical skills and technical
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mechanics (nonlinear beam theory, fluid-structure interaction) Desire to develop interdisciplinary expertise across hydrodynamics and structural mechanics. Experience with or willingness to learn: Programming
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PhD subjects, high interdisciplinary desire to learn and willingness to cooperate, very good verbal and written English communication skills. What we offer: Pioneering Research Environment: Shape
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Requirements We will only consider candidates with a good Bachelor’s degree (ideally, a first, minimum 2:1) and/or a master’s degree in computer science, data analytics, health economics, or computational
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or very-good university degree in economics, business studies, agricultural sciences with a focus in economics, or related disciplines strong analytical and methodological skills with a focus on