关注公众号,获取更多AI领域发展机会
新加坡南洋理工大学是一所科研密集型大学,有3万3千多名本科生和研究生,分布于工学院、商学院、理学院、文学院、研究生院,以及与伦敦帝国学院联合创办的李光前医学院。南洋理工大学“QS世界大学排名”第16,“US news世界大学排名”第30,是亚洲前3的大学。
导师介绍
Mengmi Zhang于2023年八月份入职新加坡南洋理工大学(school of computer science and engineering)tenure track助理教授和新加坡NRF fellow 2023。Mengmi现任新加坡科学技术研究局Agency for science,Technology and Research (A*STAR)研究科学家和PI带领Deep NeuroCognition 实验室。此前,Mengmi在2019-2021在哈佛医学院和麻省理工学院 The Centers for Brains,Minds,and Machines(CBMM)从事博士后。
Mengmi博士毕业于新加坡国立大学(2015-2019)。期间在哈佛医学院交换。她的主要研究方向在由神经学启发的机器视觉。她的交叉学科成果发表在科学杂志Nature Communications, Nature Human Behavior以及人工智能顶会和期刊CVPR,ICCV,NeurIPS, AAAI, TPAMI 等。她的研究兴趣包括并不局限于机器视觉,可持续学习,注意力机制,推理能力,记忆和储存机制,机器学习,人类行为学。
联系方式:Mengmi Zhang (a0091624@gmail.com)
博士生
Deep NeuroCognition实验室有多个博士奖学金名额,学生将获得新加坡南洋理工大学计算机科学与工程学院的博士学位。申请学生必须愿意在计算神经科学和人工智能的交叉领域从事多学科的研究项目。包括设计人类行为实验和收集人类反应,同时开发认知功能的计算模型(visual attention, eye movements, visual perception, memory, context reasoning, multi-agent decision making)。
▌计算机视觉或机器学习博士职位申请要求
语言(精通英语阅读/写作;所有一对一的会议/小组会议都用英语进行)
(可选)在ICLR, CVPR, ICCV, AAAI, ICML, NeurIPS, TPAMI, IJCV, IJCAI, WACV, ECCV, EMNLP发表过至少1篇论文(第一、第二或第三作者)
满足NTU博士申请网站中列出的标准:https://www.ntu.edu.sg/admissions/graduate/radmissionguide#Content_C047_Col00
自我过滤标准(理解下方至少9个名称即可申请否则不要):Multi-agent Reinforcement learning, deep reinforcement learning, Convolution Neural Nets, Hebbian learning, vision transformer, continual learning, scene graphs, reward, inverse reinforcement learning, backpropogation, shape bias, knowledge distillation, self-supervised learning, augmented memory, variational auto-encoder, associative memory, foveation, Blender, cause-effect, neuro-symbolic, recurrent neural networks, LSTM, Mturk, Prolific, Python, Matlab, Pytorch, Tensorflow, NVIDIA, cross-entropy, maximum likelihood, metric learning, representation learning, open-set, long-tailed, object detection, object classification, mixup, style transfer, data augmentation, curriculum learning, generalization, out-of-distribution, domain shifts, random forest, decision tree, Monte Carlo tree search, hard and soft attention, meta-learning, depth estimation, video tracking, predictive coding
▌神经科学和认知科学博士职位的要求
语言(精通英语阅读/写作;所有一对一的会议/小组会议均以英语进行)
(可选)在Nature/Science及其子刊、PNAS、Journal of Vision、PLOS computational biology、Psychonomic Bulletin & Review、Trends in Cognitive Sciences、Vision Research、Attention, Perception, & Psychophysics、Visual Cognition、Current Biology、Vision、Journal of Experimental Psychology、Psychological Review、Cognition、Philosophical Transactions of the Royal Society B: Biological Sciences、Proceedings of the xx Annual Conference of the Cognitive Science Society、PLoS ONE至少有1篇出版物(共同作者)。
满足NTU博士申请网站中列出的标准:https://www.ntu.edu.sg/admissions/graduate/radmissionguide#Content_C047_Col00
自我过滤标准(理解下方至少9个名称即可申请否则不要):eye fixations, saccades, eyetracker, Unity3D, Blender, rendering, foraging, memory, stroop test, Hebbian, virtual reality, eye movements, hippocampus, pre-frontal cortex, intuitive physics, theory of mind, Prolific, Mturk, visual search, foveation, Garbor filters, retinal ganglion cells, receptive field, on-center-off-surround receptive field, Gestalt psychology, visual illusion, synapse, Long-term potentiation, plasticity, HMAX, Matlab, Python, predictive coding
▌Mengmi也指导以下奖学金得主(non-exhaustive)和中国CSC交换生
A*STAR研究生奖学金(AGS)
新加坡国际研究生奖(SINGAPORE)
A*STAR研究实习计划(Arap)
A*STAR计算和信息科学奖学金(ACIS)。
AISG博士奖学金(AISG)
行业资助:阿里巴巴人才计划
▼ 感兴趣的学生把CV和research statement发给Mengmi (a0091624@gmail.com)
博士后/研究学者
本实验室有多个职位空缺。欢迎有认知科学和心理学经验的博士后和研究科学家,特别是视觉注意力、眼球运动、视觉感知、记忆、multi-agent 决策和推理等。也欢迎对生物视觉和认知方面的基础科学有好奇心和热情的计算机视觉和强化学习研究人员。
研究人员必须愿意在计算神经科学和人工智能的交叉点上从事多学科的研究项目。这包括设计人类行为实验和收集人类反应,同时开发认知功能的计算模型。
▌对计算机视觉或机器学习博士后职位的要求
语言(精通英语阅读/写作;所有一对一的会议/小组会议都用英语进行)
(可选)在ICLR, CVPR, ICCV, AAAI, ICML, NeurIPS, TPAMI, IJCV, IJCAI, ECCV, EMNLP上至少有4篇论文(第一作者)
自我过滤标准(理解下方至少9个名称即可申请否则不要):Multi-agent Reinforcement learning, deep reinforcement learning, Convolution Neural Nets, Hebbian learning, vision transformer, continual learning, scene graphs, reward, inverse reinforcement learning, backpropogation, shape bias, knowledge distillation, self-supervised learning, augmented memory, variational auto-encoder, associative memory, foveation, Blender, cause-effect, neuro-symbolic, recurrent neural networks, LSTM, Mturk, Prolific, Python, Matlab, Pytorch, Tensorflow, NVIDIA, cross-entropy, maximum likelihood, metric learning, representation learning, open-set, long-tailed, object detection, object classification, mixup, style transfer, data augmentation, curriculum learning, generalization, out-of-distribution, domain shifts, random forest, decision tree, Monte Carlo tree search, hard and soft attention, meta-learning, depth estimation, video tracking, predictive coding
▌对神经科学和认知科学博士后职位的要求
语言(熟练掌握英语阅读/写作;所有一对一的会议/小组会议都用英语进行)
(可选)在Nature/Science及其子刊、PNAS、Journal of Vision、PLOS computational biology、Psychonomic Bulletin & Review、Trends in Cognitive Sciences、Vision Research、Attention, Perception, & Psychophysics、Visual Cognition、Current Biology、Vision、Journal of Experimental Psychology、Psychological Review、Cognition、Philosophical Transactions of the Royal Society B: Biological Sciences、Proceedings of the xx Annual Conference of the Cognitive Science Society、PLoS ONE至少有3篇论文(合著者或第一作者)。
愿意在实验室工作至少2年
自我过滤标准(理解下方至少9个名称即可申请否则不要):eye fixations, saccades, eyetracker, Unity3D, Blender, rendering, foraging, memory, stroop test, Hebbian, virtual reality, eye movements, hippocampus, pre-frontal cortex, intuitive physics, theory of mind, Prolific, Mturk, visual search, foveation, Garbor filters, retinal ganglion cells, receptive field, on-center-off-surround receptive field, Gestalt psychology, visual illusion, synapse, Long-term potentiation, plasticity, HMAX, Matlab, Python, predictive coding