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to the Terms and Conditions regarding privacy and collection of personal information. Any applicant that does not submit the required documentation, including documentary evidence, will not be considered
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4‑year PhD position in the area of machine learning and computer simulations. The focus of the PhD project will lie on developing machine learning models for clustering, classification, regression and
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Ordinance (Chapter 12, Section 2), decisions regarding employment cannot be appealed. Further information about the position and the project is available from Professor Rikard Eriksson (project leader
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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 general planning of the PhD
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Respect at Melbourne Content warning: This website includes information on sexual harassment and sexual assault and may be distressing for some people. For support, contact the Safer Community
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knowledge. For detailed information about what the application must include, see the section "Application". Qualified applicants will be ranked according to the following criteria: In
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and experimental data, the student will develop predictive models of strand displacement reactions in non-ideal settings, in collaboration with the other students within BIOHYBRITE. These areas include
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approach, combining machine-learning–enhanced text-as-data analysis with qualitative discourse analysis. The project aims to produce a set of high-quality scholarly outputs, including peer-reviewed journal
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-based workflow including Spatial GSA and statistical methodsEnhance monitoring accuracy and validate numerical models using field data The Doctoral researcher will be supervised by Prof. Lavasan, and will
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use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission analysis, and infrared thermography. Industry