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Responsibilities Quantitative method development and computational modeling (45%) -Develop, implement, evaluate, and advance computational approaches for estimating spatially and temporally resolved air-pollutant
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Full-Time Fixed-Term for 36 months This PhD aims to develop novel robotic monitoring and data processing methods to document changes in dynamic seafloor environments over large spatial scales
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, feed composition, and variables related to production-system typologies. Develop, adapt, and apply quantitative models to assess livestock interventions, including process-based, biophysical, spatial
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models for bridging knowledge gaps, data scarcity and uncertainty gaps, and governance gaps related to monitoring the environment on which humans depend. A part of this is **spatial statistics of sensor
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repair. Our research integrates single-cell and spatial multi-omics, human developmental tissue, stem cell and organoid models, perturbation approaches, and in vivo models to uncover mechanisms controlling
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Memorial Sloan Kettering Cancer Center | New York City, New York | United States | about 22 hours ago
Role Overview: We are seeking a highly motivated computational biology postdoctoral fellow to lead translational studies in single cell and spatial biology of gastric cancer immunology and evolution
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the behavior of geotechnical systems across multiple spatial and temporal scales. Specific research areas of interest may include: advanced computational methods, constitutive and multi-physics modeling, digital
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bioinformatics for a fixed term (CDD) Research Engineer (Ingénieur d’études) position within the team. Main Mission Mammary organoid culture and bioinformatic analysis of spatial transcriptomics data. Main
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. https://eurosoho.eu/ FUTURA coordinates European modelling and infrastructure efforts to jointly develop and deploy a sustainable, aligned system for delivering future emissions scenarios, and climate and
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This PhD aims to develop novel robotic monitoring and data processing methods to document changes in dynamic seafloor environments over large spatial scales. Motivation: Understanding how