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will play a key role in ensuring that these complex data streams are acquired, synchronized, quality-controlled, modeled and interpreted with the highest level of technical and analytical rigor. Main
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at the neuro-immune interface Experimental approaches include in vivo tumour models, conditional mouse genetics, neuronal tracing, genetic and viral manipulation of neuronal populations, immune-cell depletion
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improve high-throughput experimental workflows including closed-loop thin-film optimization Apply AI and Machine Learning for data analysis and modelling Develop, improve and implement HW/SW concepts and
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London, and with a strong team of postdoctoral researchers and PhD students Generous access to frontier AI models and high-performance compute for proof-assistant workloads Funded travel for collaboration
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materials synthesis with synchrotron radiation, neutron scattering, spectroscopy and electroanalytical methods. A major research direction is the development of physical methods and models for the description
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neuroscience. Within this framework, AI models are co-developed with domain experts to unlock concrete biological questions and accelerate their translation to clinic. The large and interdisciplinary research
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experimental workflows including closed-loop thin-film optimization Apply AI and Machine Learning for data analysis and modelling Develop, improve and implement HW/SW concepts and components to automate
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Your position We combine mouse tumour models, immunology, molecular biology, flow cytometry, imaging and single-cell approaches to investigate how neurons, immune cells and stromal cells communicate
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interpretation of the results including population decoding, computational modeling of retinal circuits, and biophysical modelling. One possible research direction is to study the biophysics of the signal
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communities as a model system. Main duties and responsibilities Anaerobic digestion communities are among the best-characterized and most ecologically important microbial ecosystems. Composed of diverse