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, control theory, or a related field. Strong statistical understanding and a talent for data analysis and visualization using Matlab or Python are expected. Specific experience with experimental design
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and Python, and experience with Bayesian modelling and time series analysis. A track record of research outputs, including publications or presentations at national or international conferences. About
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and presentations tailored for different audiences. Supports performance monitoring aligned with strategic plan goals and key performance indicators (KPIs) User Support and Training Provides training
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to engage with stakeholders and partners across the water sector Strong analytical and coding skills within a package such as MATLAB, R or Python. Ability to use initiative, and apply creativity, to solve
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innovative methods for processing and analyzing 7Tesla MRI images of different modalities and formats (NIFTI, DICOM, etc.) using machine learning and artificial intelligence techniques. These methods will be
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. This research project has a dual focus. On the one hand, you will be involved in analysis of spatial, single-cell and multi-omics data to efficiently characterize the different molecular layers. This will be done
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mimicked with in vivo models of metastasis, which provides unique opportunities to mechanistically dissect what drives the different cell states. You will link clinically relevant phenotypes to putative
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research teams from different scientific cultures (ecology, physiology and ethology, chemistry and subatomic physics) develop very high level programs based on scientific instrumentation. The IPHC is
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individually, make a real difference. The role A research fellow position is available to work on the project “Dynamic and Adaptable Monitoring of Greenhouse Gas Emissions with Robots” funded by the UKRI Natural
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medicine treatment and governmental policy. The ideal candidate will have a strong background in data science, particularly in transforming datasets and creating / maintaining data pipelines across different