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strong interest in aluminum alloys, fatigue analysis, and numerical modelling is preferred. Experience with computer aided design and engineering (CAE, e.g., Abaqus, Ansys) software tools commonly used in
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innovation. This PhD opportunity is part of the Marie Skłodowska-Curie Doctoral Network UP2MEM, a European training network committed to advanced MEMbrane technologies for water and food industries. Through
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candidate in the Acoustic Technology group at DTU Electro, you will conduct fundamental research in statistical signal processing and machine learning for microphone arrays, addressing real-world challenges
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Job Description DTU, Department of Civil and Mechanical Engineering, the Section for Manufacturing Engineering invites applications for a PhD position (3 years) on the topic of simulation
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for doctoral networks, applicants must NOT yet have a PhD. You must have: A Master’s degree and/or BSc degrees in Chemical Engineering, Physics, Chemistry, Materials Science, or related disciplines. An aptitude
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cancer (SCLC). As part of the EU-funded MIPrecise network (Marie Skłodowska-Curie Actions Doctoral Network), you will develop and apply advanced mass spectrometry and nano–liquid handling workflows
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materials design, prospective life cycle assessment, and industrial innovation. This PhD opportunity is part of the Marie Skłodowska-Curie Doctoral Network UP2MEM, a European training network committed
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technologies. Responsibilities and qualifications The PhD project will focus on the design, synthesis, and characterization of new types of metal-organic network structures, which includes the detailed
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computer engineering, including artificial intelligence (AI), machine learning, internet of things (IoT), chip design, cybersecurity, human-computer interaction, social networks, fairness, and data ethics