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Field
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The research in this doctoral opportunity will develop a failure model that can represent the combined effect of surface and bending failures in gears to perform reliable health prognostics. Lack
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analysis (TEA) or an affinity towards these research questions. - Basic knowledge in bioprocess design, bioengineering and/or mathematic modeling - Affinity towards research question in life cycle
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Description As part of a multi-disciplinary, integrated research team, the candidate will participate directly in efforts to relocate seismicity and to provide subsurface velocity models and geo
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unbounded variable and instance sets. In addition, novel approaches such as Physics Informed/Guided Learning allows the learning models to capture the underlying physics/patterns and to generate physically
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Mohamed Pourkashanian, Prof Lin Ma, Dr Kevin Hughes, Prof Derek Ingham Application Deadline: Applications accepted all year round Details This project will investigate the most efficient modelling
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messengers transported by the flow or even the pressure of the fluid itself. In an interdisciplinary team, you will either develop theoretical models of the feedback between flow and network architecture
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of big data might not be possible to be captured by traditional modelling approaches. This implies that mathematical modelling of such data is infeasible. The data-driven modelling approach could resolve
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Board, India (SERB) and UBC, provides up to five scholarships per year to PhD candidates in the fields of Science, Technology, Engineering and Mathematics. Each scholarship provides four years of funding
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the 01.10.2022. Your Responsibilities: You will work at the cutting edge of privacy-preserving deep learning research with a focus on one or more of the following topics: - Optimal model design for differentially
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to familiarize yourself with methods of empirical or model-theoretical research, as well as motivation, commitment, and fun in re-search. Ambitions to pursue an academic career are welcome and will be supported