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and gene-specific approaches for determining the functional consequences of human genetic variation. Current and developing projects include massively parallel splicing assays, functional
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grow’. We welcome you to join our community of faculty, students and alumni who are shaping the future of AI, Data Science and Computing. We are seeking a motivated Research Fellow to join the Parallel
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are required. Experience in python, Fortran, C++ and parallel computing are a plus. 3. Good publication record in peer-reviewed journals for fluid mechanics. 4. A Ph.D. degree in relevant
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the laboratory, and to manage several experimental lines in parallel. It is recognised that the successful candidate is unlikely to have experience of all techniques required by the project. Full training will be
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security guarantees. In parallel, we will investigate how modern AI techniques can accelerate large-scale formal verification, developing AI proof agents that can maintain, extend and refactor the seL4 proof
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for extension to 36 months. The Research Fellow will support the development of GIS-based decision-support-tools for spatial planning, and cumulative effects assessment (CEA) of offshore wind (OW). The role will
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for spatial planning, and cumulative effects assessment (CEA) of offshore wind (OW). The role will focus on collecting, processing, and harmonising appropriate geospatial data, providing geospatial data
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work under the supervision of Prof. Stam Sotiropoulos, along with national and international collaborators (Oxford, MIT, CEA Paris). The developments in the mouse will lead to novel contrasts that carry
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work under the supervision of Prof. Stam Sotiropoulos, along with national and international collaborators (Oxford, MIT, CEA Paris). The developments in the mouse will lead to novel contrasts that carry
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these areas commensurate with career stage. Experience of FORTRAN and python programming. Previous experience in developing and using parallel computer codes using the Message Passing Interface (MPI). This is