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an exciting opportunity to work at the interface of neuro-oncology, nanomedicine, and translational cancer research, contributing to a programme with clear clinical relevance and long-term vision
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A post-doctoral Research Associate position in Neurocomputation is available to work with Prof Zoe Kourtzi at the Adaptive Brain Lab, Univ of Cambridge, UK (http://www.abg.psychol.cam.ac.uk ). Are
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learning and decision making in humans using multimodal neuroimaging (e.g. MEG/EEG, fMRI, simultaneous EEG/fMRI) and computational modelling. These projects are designed to characterize the patterns of brain
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Systems – autonomous vehicles, collaborative robots, and human–machine interaction. · Biomedical Engineering & Health Technologies – wearable devices, brain–computer interfaces, and digital health systems
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candidates in all areas of Biomedical Engineering are encouraged to apply, with strategic interest in: Bioelectronics Brain-Computer Interfaces Biomaterials and Biomanufacturing Organoids and Organ-on-a-Chip
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. They will develop code and data sharing standards for the lab, and create SOPs for interfacing with GEO and bitbucket. They will train the laboratory on code backup in bitbucket and computational lab
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funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Job description: The University
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Innovative electrical interfaces for solid-state electrocaloric cooling using ferroelectric ceramics
the developed electrocaloric material and structure within a global system incorporating the electrical driving interface, with in mind the global energy efficiency of the whole device. The application
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leadership and advocacy for strategic and fiscal planning; enrollment and curricular management; student recruitment and retention; program review and accreditation; faculty and staff recruitment, professional
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interfaces/ontologies) that make decision variables, causal pathways, assumptions, and uncertainty explicit, enabling consistent coupling of engineering and techno-economic models Data-driven and physics