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宣讲会信息
邀请对象：诚邀具有数学、统计、神经科学、生物信息、人工智能、生物医学工程、临床神经科学等相关背景、未来有意愿回国工作的博士、博士后及其他优秀学者参加本次宣讲会。
宣讲会场次（英国时间）
第一场：剑桥地区 2月7日（周二） 18:30-20:30 Richard Eden Suite (Gillian Beer House)
第二场：牛津地区 2月8日（周三）（具体时间、地点待定）
第三场：伦敦地区 2月13日（周一）（具体时间、地点待定）
宣讲会日程
1.欢迎来宾入场
2.主题报告（冯建峰院长）
3.茶歇，自由交流
4.访问团其他成员分享
5.政策答疑，自由交流
访问团成员
· 冯建峰
复旦大学大数据学院、类脑智能科学与技术研究院院长
· Gunter Schumann
复旦大学类脑智能科学与技术研究院特聘教授
· Valerie Voon
复旦大学类脑智能科学与技术研究院特聘研究员、剑桥大学教授
· 贾天野
复旦大学类脑智能科学与技术研究院青年研究员
报名方式
如您有意愿参加本次宣讲会，可通过扫描下方二维码或点击链接填写报名表。
本次活动受场地限制，名额有限，预报从速！
大数据学院简介
类脑研究院简介
聚焦五大前沿方向
认知与神经调控
从微观、介观、宏观尺度解析记忆、决策、情感等认知活动的大脑机制，探索脑功能网络协同作用机制及其在大脑高级认知功能中的作用，进而发展脑机交互智能神经调控、人机交互认知行为干预、闭环神经康复等前沿理论与技术，开展从机制、技术到应用的神经与精神疾病精准诊疗转化研究。
生物信息与脑科学
基于神经科学、认知心理学和计算科学等领域的交叉研究基础，采用蛋白、突触、神经投射、系统等多层次及分子、神经网络、行为范式等多尺度技术组合，建立和发展基于生物学基础的脑信息处理与认知原理解析理论体系。
全脑计算与类脑智能
基于脑图谱数据建立跨尺度脑网络计算模型，开展全脑尺度神经网络理论研究和仿真，模拟多种神经环路和认知功能，解析疾病的发病机制，启发类脑智能学习新理论、新算法和新框架，推进新一代人工智能理论发展。
神经影像与转化
针对多组学多模态生物医学大数据，建立和应用人工智能算法和模型，开发生物标志物和药物靶标，发展健康风险预测、智能诊疗及干预、预后评估以及智能神经调控等理论与技术。同时发展脑影像技术与转化医学，基于高场人体和动物磁共振系统，针对重大临床问题，研发新型磁共振成像技术、重建技术以及硬件；提升结构、功能、代谢等多尺度磁共振测量精度；并结合脑磁、脑电、近红外等，形成多模态脑测量体系。
类脑智能技术与应用
基于智能科学的新理论、新算法和新框架，开展脑疾病个性化医疗转化研究；研发智能感知、智能决策、智能控制理论以及新一代无人系统技术，在自动驾驶、智能制造、智慧城市等领域开展示范应用。
复旦大学大数据学院、类脑智能科学与技术研究院欢迎您的加盟。
了解最新信息请关注：
微信公众号：
复旦大数据学院
复旦类脑智能科学与技术研究院
大数据学院网站：https://sds.fudan.edu.cn
类脑中文网站：https://istbi.fudan.edu.cn
类脑英文网站：https://istbi.fudan.edu.cn/lnen/
INFORMATION
The Institute of Science and Technology for Brain-inspired Intelligence (ISTBI) ,and School of Data Science at Fudan University (Shanghai, China) will be hosting 3 recruitment sessions in UK.
Please join us if you’re interested in the convergence of Neuroscience and Artificial Intelligence and an exciting career in one of China’s biggest cities!
Any PhD candidates, postdocs, and scholars with background in Mathematics, Statistics, Neuroscience, Bioinformatics, Artificial Intelligence, Biomedical Engineering, and Clinical Neuroscience and would like to work in China are invited to the session.
British time
Session 1：University of Cambridge Feb 7 (Tue.) 18:30-20:30 Richard Eden Suite (Gillian Beer House)
Session 2：University of Oxford Feb 8 (Wed.) (Time and venue to be announced)
Session 3：London Feb 13 (Mon.) (Time and venue TBA)
AGENDA
1. Welcome
2. Keynote Presentation (Dean: Prof. Jianfeng FENG)
3. Coffee Break & Free Chat
4. Talks by Other Representatives
5. Q&A and Discussion
REPRESENTATIVES
Jianfeng FENG Dean, Distinguished Professor
Gunter Schumann, Distinguished Professor
Valerie Voon, Distinguished Research Professor at Fudan University，Professor at the University of Cambridge
Tianye JIA, Young Principal Investigator
REGISTRATION
Please scan the QR code to register to attend.
ABOUT SDS
The School of Data Science (SDS), Fudan University was established on October 8, 2015. This is a major strategic move for the time-honored university to aim at the frontier of international science and technology, focus on national innovation and development, and stimulate the dynamics of disciplines on its road to academic excellence, developing a world-class university and first-class disciplines. Committed to big data scientific research, talent training and industrial innovation, with computer science, statistics, and computational mathematics as three fundamental disciplines, SDS values in-depth interdisplinary study and practical application in subjects like information science, life sciences, medicine, economics, sociology, management, environmental science, engineering, et. SDS explores a brand-new student training method, which starts early and has an excellent system, and strives to build a solid platform for data science research and application. In the past seven years, a group of data science talents with solid basis and international vision has been nurtured to make contributions for our society.
The International Interdisciplinary Talent Team，SDS implements the tenure-track system, which is widely adopted by North American universities. The Academic Committee of SDS, composed of internationally renowned experts in the fields of computer science and statistics, including Professor Fan Jianqing, the first dean of SDS and a leading figure in international statistics, adopts an internationally advanced academic evaluation mechanism and is responsible for the recruitment and promotion assessment. SDS has now introduced 27 overseas returnees and has one academician, five national-level talent program candidates, eight National Youth Talent Program candidates, and five province-level talent program candidates. SDS has also formed the Faculty Council and Advisory Committee to guide the academic development, recruitment of talents, and student training, and enjoys an excellent practice platform and abundant research resources.
ABOUT ISTBI
Founded in June 2015, the Institute of Science and Technology for Brain-inspired Intelligence (ISTBI) is an interdisciplinary research institution of Fudan University and one of the first interdisciplinary research institutions for neuroscience and brain-inspired intelligence in China.
We are dedicated to build a world-class interdisciplinary research team that focuses on frontier fundamental research and applied research in cognitive neuroscience, computational biology, computational psychiatry, artificial intelligence algorithms, brain-inspired artificial intelligence technology and other fields, for the benefit of China and the world.
RESEARCH AREAS
Cognitive and Neural Modulation
We analyze the brain’s mechanisms of memory, decision-making, emotion and other cognitive activities at micro, meso and macro scales and explore the synergistic mechanism of the brain’s functional network and its role in the higher cognitive function. From there, we carry out translational research on the precision diagnosis and treatment of neurological and mental diseases, achieved through cutting-edge theories and technologies such as brain-computer interactive intelligent neuromodulation, brain-computer interactive cognitive behavior intervention, and closed-loop neural rehabilitation.
Bioinformatics and Neuroscience
Building on our previous interdisciplinary research in neuroscience, cognitive psychology and computer science, we combine multi-level techniques, including protein, synapse, neural projection and system, with multi-scale techniques, including molecular, neural network and behavioral paradigm, to establish a biology-based theoretical system for demystifying the brain’s principles of information processing and cognition.
Whole-brain Computation and Brain Simulation
We are studying and simulating the neural network on a whole-brain scale by using brain atlas data to build a cross-scale neural network computing model. We are simulating various neural circuits and cognitive functions, uncovering the pathogenic mechanism of brain diseases, and ultimately illuminating the path for a new theory, algorithm and framework of brain-inspired intelligence learning, so as to instigate a new generation of Artificial Intelligence.
Brain-inspired Intelligence Technology and Application
By developing new theories, algorithms and frameworks of intelligence science, we are laying the groundwork to heal brain diseases with personalized treatment. We are also developing intelligent perception, decision-making, control theories and new-generation unmanned systems that are currently applied in autonomous driving, intelligent manufacturing, smart city and other fields as pilot projects.
Neuroimaging and Translational Medicine
We are using AI algorithms and models built from multi-omics and multi-modal biomedical big data to develop biomarkers, drug targets and a range of theories and technologies, from health risk prediction, intelligent diagnosis and treatment to intervention, prognosis assessment and intelligent neuromodulation. At the same time, we are also developing brain imaging technology and translational medicine. Based on high-field and animal magnetic resonance systems, we are developing new MRI technology, reconstruction technology and hardware. We are also improving the measurement accuracy on multiple scales, including structural, functional and metabolic, while combining MEG, EEG and near-infrared to construct a multi-modal brain measurement system.