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of priority elasmobranch species in the study area, while managing and analysing large telemetry datasets, and integrating environmental/spatial data to address key research questions on species ecology and
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. The project follows a bedside-to-bench-and-back approach, utilizing human tissue single-cell and spatial multi-omics at disease remission (inflammation resolution), human tissue organoids, and the use and
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the localisation of inflammation in the joints. The project is based on a bed-to-bench-and-back approach , utilising human tissue single-cell and spatial multi-omics , engineered CAR-T cells,human organoids , and
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. This involves the development of mathematical models for signal transmission/reception, derivation of performance limits, algorithmic-level system design and performance evaluation via computer simulations and/or
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recruitment process, can be found at https://accedtp.ac.uk/, in the ‘prospective applicants’ tab. Project overview Are you interested in a PhD working on biodiversity and ecosystem service impacts
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to apply Website https://www.academictransfer.com/en/jobs/355829/postdoc-reverting-soil-sealing-… Requirements Specific Requirements You have a PhD in Geography, Spatial planning, Urban studies or a related
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levees by drying out soils, causing shrinkage, cracking, and weakening of protective grass cover, ultimately reducing their resilience. This PhD project offers the opportunity to spearhead cutting-edge
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on developing ecosystem models for high-latitude ecosystems and to scale-up these spatially as well as temporally using state-of-the-art ecosystem models. Your profile The successful applicant must have obtained
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applicant we are looking for has: a PhD in cognitive science with a focus on neuroinformatics, neurorobotics, cognitive modelling or related areas. experience of research and/or studies in the above-mentioned
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-seq, ATAC-seq, spatial transcriptomics, …) into modeling and develop efficient data/training pipelines Drive application cases with Helmholtz Munich, MDC Berlin, and NVIDIA—for example, disease modeling