LSI Doctoral Training Centres - Neuroinformatics and computational neuroscience

LSI 博士培训中心 - 神经信息学和计算神经科学

• 批准号: EP/F500386/1
• 负责人: David Willshaw
• 金额: $ 609.44万
• 依托单位: University of Edinburgh
• 依托单位国家: 英国
• 项目类别: Training Grant
• 财政年份: 2008
• 资助国家: 英国
• 起止时间: 2008 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FF500386%2F1
• 关键词: LSI; Doctoral; Training; Centres; Neuroinformatics

Students in the DTC will perform multidisciplinary research at the interface between EPS and neuroscience. Specific thematic research areas to be covered include: I) Computational neuroscience: analytical and computational models to gain quantitative understanding of the computations performed by the nervous system. 2) Clinical imaging algorithms and tools: advanced data analysis, such as machine learning and Bayesian approaches to improve diagnosis based on imaging techniques such as human MRI. 3) Software systems and applications: to develop intelligent computer interfaces and software that deal better with real-life data using neuroscience insights. 4) Cognitive science: to study and analyse human cognitive processes in computational terms. 5) Neuro-robotics and VLSI: to build better hardware using findings from neuroscience, e.g. robots that work under natural conditions. These areas are supported by a large number of staff with strong research programmes and many interdisciplinary centres across the university.The impact of neuroinformatics is rapidly growing, with extensive benefits to basic science, health, and technology. There is a critical need for a centre delivering multidisciplinary training in neuroinformatics and computational neuroscience. The UK is a world leader in computer science and neuroscience research, yet there is only limited PhD training available that links these areas. A specialized doctoral training centre will allow the UK to capitalize on these strengths.

DTC的学生将在EPS和神经科学之间的接口进行多学科研究。具体的专题研究领域包括：I）计算神经科学：分析和计算模型，以获得神经系统执行的计算的定量理解。2)临床成像算法和工具：先进的数据分析，如机器学习和贝叶斯方法，以改善基于成像技术（如人类MRI）的诊断。3)软件系统和应用：开发智能计算机界面和软件，利用神经科学的见解更好地处理现实生活中的数据。4)认知科学：用计算的术语研究和分析人类的认知过程。5)神经机器人和超大规模集成电路：利用神经科学的发现构建更好的硬件，例如在自然条件下工作的机器人。这些领域得到了大量员工的支持，他们拥有强大的研究项目和大学内的许多跨学科中心。神经信息学的影响正在迅速增长，对基础科学，健康和技术产生了广泛的影响。目前迫切需要一个提供神经信息学和计算神经科学多学科培训的中心。英国在计算机科学和神经科学研究方面处于世界领先地位，但只有有限的博士培训可以将这些领域联系起来。一个专门的博士培训中心将使英国能够利用这些优势。