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starting as soon as possible. The location of work can be Oxford or CERN. To develop the design and the technology of the vertex detector for LHCb Upgrade II through the TDR phase. The successful candidate
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to develop coupled sub-models within a system dynamics framework. Working with colleagues from the Karlsruhe Institute of Technology, the candidate will build a behavioural sub-model using the CRAFTY GB model
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This is an exciting opportunity for a skilled and motivated researcher, with an interest in working at the interface of biopolymer chemistry and process engineering. This project aims to develop
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starting as soon as possible. The location of work can be Oxford or CERN. To develop the design and the technology of the vertex detector for LHCb Upgrade II through the TDR phase. The successful candidate
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the changing geography of computational infrastructures and understanding how it is shaped by the interaction of technology companies’ business interests and states’ economic and security interests. The project
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cell biology; cancer; cardiovascular; nutrition and diabetes; genetics; infection and immunology; imaging and biomedical engineering; transplantation immunology; pharmaceutical science; physiology and
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dynamic strain and flow fields during flight. Candidates should hold a PhD in a relevant biology or engineering discipline and be competent with numerical simulations. Desirable competencies would include
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should have a recent doctoral degree in electrical engineering, control engineering, or a related field. For the physics-informed AI position, a doctoral degree in computer science or applied mathematics
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to develop coupled sub-models within a system dynamics framework. Working with colleagues from the Karlsruhe Institute of Technology, the candidate will build a behavioural sub-model using the CRAFTY GB model
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—an ambitious, EPSRC-funded initiative led by Dr. Sina Sareh, Academic Leader in Robotics. We are looking for a highly skilled researcher with expertise in robotics, AI, software engineering, or computer science