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Field
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officially awarded their PhD will be appointed as Research Assistant. Expertise in geospatial data analysis, including remote sensing Expertise in cloud physics, preferably cirrus clouds Aircraft performance
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Location: South Kensington About the role: The role will develop new AI methods for identifying the instantaneous state of a fluid flow from partial sensor information. The research will couple
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Strong analytical and problem-solving skills. Proficiency in data analysis software (e.g., R, Excel). Excellent written and verbal communication skills. Ability to work independently and as part of a team
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Europe | 23 days ago
4 Doctoral Candidate (DC) positions as part of the Horizon Europe MSCA-DN program, focusing on cutting-edge Multicore Fiber Applications and Technologies.DC 1 – OpenProject Title: Impact of extra
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for spectroscopic analysis Analyze data and collaborate with project partners Maintain and operate advanced spectroscopic instrumentation Assist in laboratory organization and support training of junior researchers
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seeking exceptional researchers to join our dynamic team. As a Machine Learning Researcher, you will apply advanced ML techniques to a wide range of forecasting challenges, including time series analysis
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in regular team meetings and contribute to data analysis discussions. Work can be completed remotely/hybrid Qualifications Enrollment in a PhD program in education, social sciences, or a related field
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, where opportunities for collaboration and learning abound. About the role The role involves undertaking high quality research as part of an exciting new internationally funded research project
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prototypes, conducting laboratory and field evaluations, and analyzing experimental data. The role also involves preparing technical documentation and contributing to scientific publications. Organizational
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. Laboratory and Field Testing: Evaluate sensor performance in laboratory settings and conduct field testing to validate sensor functionality. Data Management and Analysis: Compile and analyze experimental data