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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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interested in a longer-term commitment in a growing research group and you are willing to work in close cooperation with industry. You are fluent in English, both spoken and written. Further information is
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PhD degrees in computer science, a BSc in artificial intelligence, and an MSc degree in data science. The project is supervised by Stelios Tsampas (stelios@imada.sdu.dk ) and Marco Peressotti
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in relation to the department – internally as well as externally – and to contribute positively to the department’s working environment, everyday life and ongoing operation. More information about our
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are developed, modelled and controlled. You will create novel adaptative, physics-informed models that tightly integrate thermo-fluid dynamic laws, deep learning neural networks, and experimental data. A key
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of state-of-the-art imaging technologies, high resolution single cell data sets that will be established on non-trial samples. The PhD will include bioinformatic support from internal and international
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(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. MYC activity at enhancers drives
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Helicobacter pylori bacteria interact with each other and their host in a gastric organoid and organoid-derived monolayer cell culture system. Information on the department can be found at https://globe.ku.dk
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career development. Training in state-of-the-art technologies and data analysis as well as research management, oral and written communication. Participation to international conferences to facilitate
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sequencing data is an advantage. We offer: A three-year PhD position (or four-year for Master students) in a supportive, stimulating, and interdisciplinary research environment Enrollment in PhD school