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components are in use. More specifically, the PhD position will look towards connecting different advanced software tools (of multi-physics and data-based models) simulating the metal AM process
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Job Description If you are ready to launch your research career in advanced manufacturing and want to build cutting-edge skills in AI and real-time data-driven production, this PhD opportunity is
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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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the absolute forefront of observing and modeling two of Greenland’s largest glaciers -- Jakobshavn Isbræ and the Northeast Greenland Ice stream (NEGIS). You will use GNSS data on ice surface and bedrock
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conceptual framework linking nanoscale features to macroscopic adsorption efficiency. Generate and curate high-quality datasets to support data-driven materials optimization and future integration with AI
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. You should have a strong academic background in engineering, applied mathematics, or computer science, combined with a clear interest in scientific programming, machine learning, and data analytics
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the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see DTU's
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: They are responsible for the central tasks of storing and processing quantum information. The memories must be optically active so distant nodes in a network can be entangled via single photons emitted by the memories
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communication skills in English are essential. Application The application must contain: A cover letter of max. 1 page, including (i) motivation for applying, (ii) preferred starting date (specifically if other