Sort by
Refine Your Search
-
committed to embedding good equality and diversity practices into all our activities so that the university is an inclusive, welcoming, and inspiring place to work and study, regardless of age, disability
-
students, 150 postgraduate students, 200 PhD students and 110 teaching and research staff. Details about SBBS can be found at https://www.qmul.ac.uk/sbbs/ About Queen Mary At Queen Mary University of London
-
Modernising Medical Microbiology (MMM) unit at the University of Oxford (https://www.expmedndm.ox.ac.uk/mmm). You will be joining a highly interdisciplinary team of approximately 40 clinicians, computational
-
become an embedded member of both teams, joining a Senior Research Fellow and PhD student who engage in cross-technique research in a clinical setting. The hyperpolarised groups are strategically placed
-
to advanced control design and system optimization. Our specialty is developing embedded control, estimation, and identification algorithms that directly interface with physical hardware. We work closely with
-
provide an industrial assessment of the mission concept. The project will be embedded within the Space and Exploration Technology Group (SET), which comprises expertise across access to space, orbital
-
Modernising Medical Microbiology (MMM) unit at the University of Oxford (https://www.expmedndm.ox.ac.uk/mmm). You will be joining a highly interdisciplinary team of approximately 40 clinicians, computational
-
women's health. We also have thriving research programmes in global health, and health and social care. Further information about the Faculty of Life Sciences and Medicine may be found at https
-
; physiology and women's health. We also have thriving research programmes in global health, and health and social care. Further information about the Faculty of Life Sciences and Medicine may be found at https
-
levels. The candidate is expected to: Build models embedding dynamics and flexibility of process operations and related supply chains Combine analytical and data-driven surrogate models in optimization