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to computational problems Ability to code in a programming language to solve computational problems Awareness of computational infrastructure and its upkeep Ability to work on multiple projects in parallel and set
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solve computational problems Awareness of computational infrastructure and its upkeep Ability to work on multiple projects in parallel and set priorities Willingness to provide training to staff and
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the experimental data and the concepts of neuronal coding, and Elephant Analysis of the parallel rate data for submanifolds and their temporal dynamics during behavior Leverage dimensionality reduction and
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related in space and time and to behavioral events. Core Tasks: Getting familiar with the experimental data and the concepts of neuronal coding, and Elephant Analysis of the parallel rate data for
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strong background in applied mathematics Excellent programming skills (Python, C/C++) Good experience in machine learning and parallel computing Good organisational skills and ability to work both
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(if designated). If you close the browser or exit your application prior to submitting, the application process will be saved as a draft. You will be able to access and complete the application through “My Draft
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experience in machine learning and parallel computing Good organisational skills and ability to work both independently and collaboratively Experience with deep learning frameworks, such as Tensorflow
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process and in conjunction with a Clarendon Fund Scholarship. To be considered for this scholarship, you must submit your application for graduate study by the relevant December or January deadline (please
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funded by the University and by NaturalMotion Ltd. NaturalMotion Ltd develops computational methods for animating movement, as used in Hollywood films and computer games. The founder, Torsten Reil, is an
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Summary This scholarship is available for Masters students (Mathematics and Statistics) undertaking research in the area of Statistics, Applied Probability, Stochastic Processes or Operations Research