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of developing ethics plans and obtaining ethics approval; data collection/analysis; experience of working in a multi-disciplinary environment and coordinating work across research partnerships; an evidenced
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Research Assistant/Assistant Professor (Postdoctoral Researcher) for the project 2025/57/B/NZ8/03444
sciencesEducation LevelPhD or equivalent Skills/Qualifications Knowledge and experience in the following areas: processing, analysis and interpretation of remote sensing data, in particular airborne laser scanning
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related discipline. A PhD in one of these fields and proven experience in programming for data analysis are required. Previous experience in neurophysiological data analysis (scalp EEG, intracranial
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energy sector, aimed at publication in top-level journals. More up-to-date information about the Chair group is available at www.ep.mgt.tum.de/pur/ Tasks The successful candidate is expected to actively
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, and from South Asia to the Mediterranean, Europe and the British and Irish Isles, including a strong suite of research projects in the Middle East. For further information on our current projects
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facilities for data acquisition v) Contribute to the analysis of structural data vi) Contribute to the dissemination of results (rapid publication expected) The project will be carried out at IGDR (Rennes
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-throughput lipid residue analysis, involving GCMS and GC-c-IRMS. They will work on the interpretation of the data and integration with other sources of evidence provided by the rest of the project team. Skills
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, clinical, and longitudinal follow-up data, including statistical modelling and survival analysis. Process, curate, quality-check, and analyse DICOM imaging datasets across modalities including DBT
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research. Responsibilities : Develop and apply machine learning and data-driven methods for the analysis and interpretation of synchrotron X-ray scattering data, including diffraction and total scattering
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blood samples to advance patient care. This role will involve developing computational models (statistical, machine learning, etc.), and using them to perform high throughput analysis of clinical data