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develop AI models to predict and study the tumor evolution and lineages using the multiomic measurements from both bulk, single-cell, and spatial technologies. The lab emphasizes understanding
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methods for use across developmental biology and more widely. Current activity involves work on the following aspects: development of new techniques for assessing and modelling the states and dynamics
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techniques to measure nutrient availability, soil microbial activity, and plant responses. Data management and analysis: Collect, manage, and analyze experimental data using statistical and modeling tools
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device fabrication and modelling or related areas. You will focus on a range of liquid crystal-based technologies and work on the optics, design, fabrication, optimisation, modelling and characterisation
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parallel, a numerical model representative of the developed materials will be created. Work plan: The work plan foreseen for the research grant has been designed to support the experimental research
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or translational research experience Knowledge of machine learning, Bayesian modeling, or statistical method development Ideal Personal Attributes: Independent, proactive, and scientifically curious Detail-oriented
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challenges from low carbon shipping and sustainable fuels to solar power technologies and advanced brain models. Learn more at https://mecheng.ucl.ac.uk . Within this dynamic environment, the Moazen Lab is
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are invited for a Research Fellow in the area of sustainable built environment. The successful applicant will work as part of the EPSRC project sChOOL YARD: Outdoor thermal comfort models for children
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modelling of cohort studies to identify risk factors and produce individual and population-based estimates. Participate in and/or present at conferences and/or workshops relevant to the project as required
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mountain catchments. The goal is to understand long-term changes in runoff regimes and flood hazards by combining climate-driven (glacier-)hydrological modelling with reconstructions of past flood events