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the project, making sure the two parts run smoothly in parallel. Preparation of manuscripts for publication in reviewed journals, on the basis of the research results obtained. Communication of research results
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in AI to study natural and artificial minds in parallel, creating the opportunity to make discoveries about ourselves and to find new ways to understand and improve AI systems. Appointments will be
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of central London. For more information: https://www.kcl.ac.uk/engineering About the role This role will support the delivery of a mesh generation project, funded under a recent major £7m EPSRC Programme Grant
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. More information about the lab and their work can be found by visiting https://www.hhmi.umbc.edu . About the Postdoctoral Scientist role: We are seeking a motivated and creative Postdoctoral Scientist
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programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Your tasks: Developing optimization algorithms for massively parallel hardware architectures such as AI
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | about 13 hours ago
architecture, health informatics, data privacy Computational Science: scientific computing, high-performance computing, large-scale parallel systems, modeling and simulation, bioinformatics, computational
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Declaration of interest regarding PhD project within the field of biomarker and therapeutic targe...
. The PhD student will work with patient cohort to perform biomarker analyses and statistical modeling of clinical outcomes. In parallel, the student will contribute to the development and validation of novel
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conventional production hosts. In parallel, we design and build advanced yeast cell factories. By combining fundamental biology with cutting-edge strain engineering, our work aims to enable sustainable
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invested in new laboratories and maker space at the centre of the Strand campus in the heart of central London. For more information: https://www.kcl.ac.uk/engineering About the role This role will support
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(fastest execution) for a given Tiramisu program, many code optimizations should be applied. Optimizations include vectorization (using hardware vector instructions), parallelization (running loop iterations