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will analyse quantitative imaging data from a variety of sources, including Spatial Transcriptomics and Multiplex Immunofluorescence platforms, for validation and calibration of mathematical models. You
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spatially-resolved models of metastatic outgrowth in the liver which account for interactions between stromal, immune and tumour cells. You will analyse quantitative imaging data from a variety of sources
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Experience in statistical or scientific programming (ideally R and/or Python) Experience in analyzing large and/or complex datasets Interest in quantifying uncertainties for computer models and/or climate
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29 Aug 2025 Job Information Organisation/Company KINGS COLLEGE LONDON Research Field Biological sciences Researcher Profile Recognised Researcher (R2) Established Researcher (R3) Country
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). This position is funded by King’s Climate and Sustainability. The key responsibilities of the role are to develop machine learning emulators of multiple ice sheet and glacier models, using ensembles
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with a PhD in Engineering (or close to completion) may apply. You will be responsible for: Design of the first reconfigurable robotic matter in collaboration with world-leading universities and
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of Engineering and Physical Sciences at HWU. The position is open in the context of a large research project aiming to develop a new generation of computational imaging algorithms intended to deliver
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resilience. We will use duckweed as a model to frame this question. In addition to being a model species, duckweed is also emerging as a promising new protein source that does not require arable land
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samples and disease models. Working closely with a dynamic and multidisciplinary team of clinicians and scientists, you will help generate and interpret high-resolution datasets that reveal new insights
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modelling, advanced AI algorithms, and decision-support tool development for various hydrogen technologies-based energy systems. Responsibilities will include programming, analysing and interpreting data, and