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inversion techniques and signal processing. Strong programming skills, Proficiency in scientific computing (e.g. Python, MATLAB, or similar) for algorithm development and data handling. Experience with sensor
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. Supervising students on research-related work and providing guidance to PhD students working alongside the project team. Undertaking administration arising from the research project and help anticipate and
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Supervise students on research related work and provide guidance to PhD students where appropriate to the discipline Contribute to developing new models, techniques and methods Undertake management
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interpretation of spectroscopic observations Analysing and interpreting research findings and results Publishing results and presenting them at conferences Role requirements include: PhD in astrophysics/astronomy
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findings for publication, including research seminars and conferences Supervise students on research related work and provide guidance to PhD students where appropriate to the discipline Contribute to
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predictions and to generate hydrological forecasts. The RF will be part of a research environment with strong ML activities. The post is mainly part of the project ‘HEavy Precipitation forecast Post-processing
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provide guidance to PhD students where appropriate to the discipline Contribute to developing new computational models, techniques and methods Undertake management/administration arising from research
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publications Supervise students on research related work and provide guidance to PhD students where appropriate to the discipline Contribute to developing new models, techniques and methods Undertake management
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related work and provide guidance to PhD students where appropriate to the discipline Contribute to developing new models, techniques and methods Undertake management/administration arising from research
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guidance to PhD students where appropriate to the discipline Contribute to developing new models, techniques and methods Undertake management/administration arising from research Contribute to Departmental