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particular, the research project will focus on inferring trajectories from spatial transcriptomics data modelling at the same time the cells evolution in gene expression and in space. Required skills : We
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approaches. The PhD will develop and apply optimization-based energy system models to analyse whether spatially coherent urban and energy configurations can be operated efficiently under realistic physical
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applications, agricultural monitoring and modeling, Agro-AI/ML, or digital twin. Instructions to Applicants: For full consideration, applicants must apply for the Research Assistant Professor at https
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individuals who have or will soon receive a PhD in Economics focusing on firm dynamics, structural transformation, economic growth, spatial economics. The appointment is for 3 years and will begin September 1
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Experience with mouse models of Alzheimer’s disease (e.g., 5XFAD). Background in MR1/MAIT cell biology and other innate immune axes. Experience with neuroinflammation assays, imaging, or single‑cell/spatial
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high potential for progression. The aim of the project is to develop an innovative in vitro model enabling investigation of the (micro-)invasion process in DCIS and identification of molecular markers
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to climate change and variability Hydrological processes in organosols and peat-affected soils Modeling Hydrological Extremes Using Machine Learning Spatial and time distribution of precipitation within
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and transcriptomics. Analyzes spatial transcriptomic datasets to uncover tissue organization and disease states. Develops integrative models combining genomics with pathology images or time-series data
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. Spectral dynamics of the conditional Lyapunov vector (https://www-cambridge-org.sheffield.idm.oclc.org/core/journals/journal-of-fluid-mechanics/article/spectral-dynamics-and-spatial-structures
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, or probabilistic modeling, and be proficient in Python and modern machine-learning frameworks (ideally PyTorch). Experience with single-cell transcriptomics, epigenomics, proteomics, spatial omics, or multimodal