26 neuroscience "Wellcome Sanger Institute" positions at University of Sheffield in United Kingdom
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Science PhD Studentship, starting in October 2024. The successful candidate will join an established training programme at the Sheffield Institute for Translational neuroscience (SITraN) in the laboratories
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programme at the Sheffield Institute for Translational Neuroscience (SITraN) in the laboratories of Prof Kurt De Vos (https://www.sheffield.ac.uk/smph/people/neuroscience/kurt-de-vos) and Dr Andrew Grierson
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, laminins, proteoglycans and entactin/nidogen. As a PhD candidate involved in this project, you'll be able to participate in pioneering research at the forefront of gene therapy and translational neuroscience
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of feedback are most useful for stroke survivors. The successful PhD candidate will work alongside academics in Neuroscience and Rehabilitation, the Deep End Research Alliance, the South Yorkshire Digital
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This project will study mechanisms for making effective collective group decisions to achieve goals that are embedded in space, drawing on inspiration from animal behaviour and neuroscience to design algorithms
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the objectives of the project. Website links Link 1: http://sitran.org/people/azzouz/ Link 2: https://www.sheffield.ac.uk/smph/people/neuroscience/arshad-majid Link 3: https://www.sheffield.ac.uk/smph/people
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: www.shef.ac.uk/postgraduate/research/apply Please clearly state the prospective main supervisor in the respective box and select Neuroscience as the department. Enquiries: Interested candidates should in the first
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-Masters degree in a science or engineering field, especially computer science, mathematics, physics, or neuroscience (2(i) / Merit or higher) -An interest in animal behaviour / computational neuroscience
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the prospective main supervisor in the respective box and select SMPH Neuroscience as the department. Funding Notes Proposed start date: 01/10/2024 Salary/stipend rate: Standard UKRI rates at Home Student rates
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applications. He has particular interests in unconventional machine learning algorithms, computational modelling of physical systems and how paradigms from neuroscience can lead to new ways of computing. His