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Field
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Python programming. Application procedure The application should be written in English be attached as PDF-files, as below. Maximum size for each file is 40 MB. Please note that the system does not support
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monitoring. Familiarity with tools such as Python, MATLAB, or embedded C would be advantageous. Most importantly, this project is ideal for applicants who are motivated to tackle real-world reliability
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considered. Experience of using machine learning algorithms and toolsets, ideally in a research context. Strong programming skills (e.g., Python, Java, C++). An interest in physiological signals. Home Student
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skills in one or more languages (Python, C/C++, or others) experience in mechanical testing profound knowledge of machine learning methods (e.g., neural networks, Gaussian processes, active learning
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marine power and control systems. Interest and experience with experimental work and laboratory-based research. Proficiency in data analysis and relevant programming tools (Python, MATLAB, etc.). Relevant
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the coupled aerodynamic, structural and thermal analysis of interface regions, for example between fins and fuselage, in hypersonic vehicles. This will involve the use and augmentation of in-house python-based
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experiences in working with remote sensing data, climate data and programming skills (R or Python) are desired. You enjoy working in an international team and you are keen on developing a key set of research
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prior experience in at least three of the following areas: Python programming Develop LLM-based tools to automate data connector generation for data ingestion. Design and implement a multi-layered storage
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Engineering, Physics or Materials Science Excellent English written and spoken communication skills The following skills are also highly desirable: Ability to program in Matlab, Python or similar Strong
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highly desirable: Ability to program in Matlab, Python or similar Strong laboratory-based skills Application Procedure Informal enquiries are encouraged and should be addressed to Prof Daniel Eakins