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Field
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rheometer cartridge in which optical fibres are integrated close to the lubricant flow channel. This will enable spatially resolved measurements of pressure and temperature profiles under extreme operating
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learning frameworks such as PyTorch or TensorFlow is an advantage); Affinity with probabilistic modelling and spatial data analysis; Interest in the physical behaviour of water systems and hydrology (prior
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and from adaptive building to spatial dispersal policies) – feed through to interest rate premia for a country on the capital market, capital requirements for banks and insurers, the investment climate
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programming skills (Python; familiarity with deep learning frameworks such as PyTorch or TensorFlow is an advantage); Affinity with probabilistic modelling and spatial data analysis; Interest in the physical
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and apply machine learning and deep learning models to analyse complex, multi-dimensional datasets, including spatial transcriptomic, proteomic, and single-cell sequencing data. The candidate will
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new method to study human pancreatic tissue slices using high-resolution calcium imaging in combination with spatial transcriptomics. The researcher will develop methods to improve the viability
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(see references below), we want to open a new route to synthetic cells and to their spatial organization: high-resolution 3D printing to enable placement with µm precision into controlled landscapes and
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shaped by adaptation and spatial dynamics. To achieve this aim, the candidate will conduct lab experiments ranging from simple bioassays to complex metacommunity experiments. Secondments on pulse
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assemblies to determine how spatial organization, cell–material interactions, mechanics, and molecular communication shape emergent behavior. Possible project elements include: Mammalian cell culture and
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project probes electrostatic potentials and charge carrier dynamics with high spatial and temporal resolution, aiming to identify efficiency-limiting recombination and defect-related effects. Preparation