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Field
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interested in candidates eager to explore the interface between cell wall mechanics and soil physical properties applying spatial gene regulation to understand root biomechanics. This position is ideally
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. Strong programming skills in languages like Python or R. Professional experience in the application of Machine Learning algorithms in the mapping and correction of spatial data. Professional experience in
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“Enhancing Machine Learning Approaches for Spatially Dependent Data in Fisheries and Environmental Research” (CMAT, University of Minho), reference 2024.15617.PEX, financed by national funds through
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Doctoral (PhD) Candidate to join the new MSCA Doctoral Network FairCFD (https://www.imft.fr/faircfd/project-presentation/ ). The candidate will enrol for a PhD in Chemical Engineering at the University
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eager to explore the interface between cell wall mechanics and soil physical properties applying spatial gene regulation to understand root biomechanics. This position is ideally suited to a highly
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to sign the contract. More information is available on: https://www.dges.gov.pt/pt/pagina/reconhecimento . Workplan and the objectives to achieve: This work aims to develop a numerical approach based on
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for gene regulatory networks, single-cell multi-omics integration, spatial omics, and variant effect mapping in complex disease. Strong method/tool dev experience required (Python/R, ML/stats
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. Procedure Reference: IT137 -26-[ARdS1.1]6 I - Legal admission requirements I.I - Grant Recipients: Master’s degree holders, in the scientific area of Natural Sciences, Biology, Ecology or Spatial Data
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cultural diversity and urban public space. The fellow will support the implementation of research activities across three main themes: 1. Urban Landscape Mapping – assisting in the collection and spatial
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activities through field surveys and data analysis; 4. collection, processing and analysis of samples for environmental DNA (eDNA) aimed at species detection and spatial distribution assessment; 5. performance