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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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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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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
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pave a path to clinical applications. This project is flanked by basic research projects i) investigating of the role of phosphoinositide 3-kinase (PI3K) signaling in allergy, metabolic control, obesity
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computational modeling, mathematical modeling, or experimental psychology. Profile We thrive on interdisciplinary collaboration. You should hold a PhD in musicology, computer science, cognitive science
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motivated Postdoctoral researcher (W/M) to join our Neuroengineering Laboratory at EPFL (https://go.epfl.ch/ramdya/ ) to work on an ERC funded project aiming to reverse-engineer insect limb motor control
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and how neuro-immune communication contributes to inflammatory or tumour-associated disease states. Approaches include neuronal tracing, in vivo disease models, genetic and viral manipulation