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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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indicated research directions This description should outline the applicant’s thoughts and ideas within the overall aim of the S4OS project. CV. Diploma and transcripts of records. Other relevant information
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The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the
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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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starting date 1 October 2025 For further information please contact Erik Kristensen, tel.: +45 6550 2754, e-mail: ebk@biology.sdu.dk Application, salary etc. Appointment as a PhD Research Fellow is for three
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-disciplinary teams. The preferred candidate has a strong interest in advanced manufacturing of mechanical and electrical products and competencies in applying life cycle assessment (LCA) data to derive decision
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. Responsibilities The role in AM2PM, an EU funded research project, involves conducting innovative theoretical and experimental research in Building Information Modeling (BIM), Digital Twin Construction (DTC
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in functional genomics methods (e.g., single-cell and bulk RNA-seq, ATAC-seq and ChIP-seq) and computational data analysis is considered highly advantageous. Selected references: Jakobsen et al., 2024
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Keysight, Denmark. Research line 2: "Energy-efficient Sensing and Computing in 6G networks" is dedicated to the interplay of data collection/sensing, communication, and computing according
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learning approaches and develop a theoretical understanding potentially based on differential geometry. In particular, deep neural networks perform surprisingly well on unseen data, a phenomenon known as