科研实习 | 约翰霍普金斯大学Alan Yuille教授招收CV方向暑期科研实习生

合适的工作难找？最新的招聘信息也不知道？

AI 求职为大家精选人工智能领域最新鲜的招聘信息，助你先人一步投递，快人一步入职！

Johns Hopkins University

The main goal of the CCVL (Computational Cognition, Vision, and Learning) research group is to develop mathematical models of vision and cognition. These models are intended primarily for designing artificial (computer) vision systems. Learning is required for extracting knowledge from data. Practical applications include vision for the disabled. These models also serve as computational models of biological vision which can be tested by behavioral methods and, in collaborative projects, with invasive, and non-invasive neuroscience techniques. We also study how humans and animals perform cognitive tasks such as learning and reasoning. In addition, we also use machine learning for interpreting medical images and studying brain function.

Advisor Profile

Professor Alan Yuille is a Bloomberg Distinguished Professor in the Department of Computer Science and the Department of Cognitive Science at Johns Hopkins. He published many influential papers in computer vision, cognitive science, etc. He has won the ICCV Marr Award and is an IEEE Fellow.

Lab Page:

https://ccvl.jhu.edu/

Overall Information

We are seeking several summer research interns for 2024. The internship starts in May, and the duration is flexible (between 6 months to 1 year). Exceptional interns from previous years have been published as the first authors at top conferences in computer vision or medical image processing, such as CVPR, ICLR, and MICCAI. Priority will be given to exceptional interns for Ph.D. applications.

Research Directions

Our lab’s research lies in computer vision and machine learning. The detailed research groups include: 3D generative models, 3D datasets, Medical image analysis, Transformers, Vision and language, Embodied AI (mentored by Prof. Tianmin Shu).

Requirements

The applicants are expected to fulfill one of the following group’s requirements. Besides, we would really appreciate it if you could specify which group you’re interested in when submitting your applications. We strongly enough you to read the related papers of our group and learn some preliminary knowledge by checking our publication list:

https://ccvl.jhu.edu/publication/

The requirements for different groups are as follows:

1. 3D generative models:

Basic: basic usage of PyTorch;

Basic: understanding of the 3D imaging (camera system);

Preferred: Publications (can be under review) on related topics, e.g., NeRF, 3D reconstruction, pose estimation, 3D detection, etc.

Understanding recent 3D vision or reconstruction techniques.

At least one of the following topics:

3D from images (pose and shape, 3D detection)
Differentiable rendering (e.g., PyTorch3D, Gaussian Splatting)
Other 3D-related topics

2. 3D datasets:

Basic skills in using Python, PyTorch, and other machine-learning libraries;

Basic skills in using 3D tools, e.g., Blender.

3. Medical image analysis:

Proficiency in computer vision and image analysis concepts;

Proficiency in Python programming to use prevalent frameworks (such as nnU-Net and MONAI);

Prior experience with the analysis of radiological image datasets for AI applications is preferred;

Relevent publication/submission in conferences/journals (such as MICCAI, TMI, and MedIA) is preferred.

4. Transformers:

Basic skills in using Python, PyTorch, and other machine-learning libraries;

Basic mathematics foundations in related areas, e.g., statistical learning and optimization;

Knowledge of the basic concepts of the Transformers architectures;

Publications or submissions in related conferences and journals, e.g., CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, TPAMI, IJCV, JMLR.

5. Vision and language:

Proficiency in using Python, PyTorch, and other machine-learning libraries;

Basic knowledge in common deep learning methods in image understanding, language modeling, and multimodal learning (E.g. CNN, LSTM, Transformer);

Understanding the concepts of generative learning and the attention mechanism with transformers;

Hands-on experience with the vision-language model or large language model (e.g., CLIP, GPT, LLAMA, BLIP, Flamingo, StableDiffusion…);

Publications or submissions in related conferences or journals, e.g., CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, TPAMI, IJCV, TMLR.

6. Embodied AI (mentored by Prof. Tianmin Shu):

Basic skills in using Python, PyTorch, and other machine-learning libraries;

Experience or interests in the following topics:

Generative AI for developing embodied simulators with diverse and realistic human behaviors, including but not limited to synthesizing human-object interactions in household environments, human-vehicle interactions, and physically grounded social interactions.
Multimodal theory of mind reasoning for embodied agents.Embodied human-AI cooperation and communication.

How to Apply

If interested, please email Professor Alan Yuille ([email protected]) with your resume attached. Interns will collaborate with Professor Alan Yuille, Professor Tianmin Shu, and their research teams at Johns Hopkins.

实习内推

腾讯IEG光子工作室群｜微软亚洲研究院自然语言计算组｜粤港澳大湾区数字经济研究院｜好未来AI增长实验室｜腾讯混元大模型团队｜微软亚洲互联网工程院｜AMD北京AI算法团队｜Apple中国NLP团队｜右脑科技｜途深智合｜微软亚洲研究院自然语言计算组｜上海人工智能实验室｜百川智能｜阿里通义实验室｜百度文心团队｜微软WizardLM大模型团队｜腾讯大数据平台混元AIGC团队｜度小满科技数据智能应用部｜阿里巴巴高德地图｜百度文心一言团队｜华为诺亚方舟语音语义实验室｜高通中国研究院｜昆仑万维AI游戏团队｜小红书社区搜索组｜阿里达摩院多模态团队｜美团NLP中心｜上海算法创新研究院｜蔚来汽车｜上海市数字医学创新中心｜联想研究院｜阿里通义XR实验室｜阿里淘天集团｜蚂蚁集团机器智能团队｜华为诺亚推荐搜索实验室｜微软亚洲研究院DKI组

校招岗位

社招岗位

高校招生

华盛顿大学计算机系王晟老师｜香港科技大学（广州）骆昱宇老师｜伊利诺伊大学香槟分校张欢老师｜西湖大学机器智能实验室｜新加坡国立大学尤洋老师课题组｜清华大学信息国家研究中心｜香港理工大学Boris NG教授｜香港科技大学（广州）张延林老师｜香港科技大学（广州）谢思泓教授｜北京大学王乐业老师｜伊利诺伊大学香槟分校张潼教授｜香港科技大学（广州）孙莹老师｜伊利诺伊理工大学王韧老师｜香港中文大学（深圳）濮实老师｜新加坡管理大学何盛烽副教授｜香港科技大学（广州）赵航老师｜南方科技大学视觉郑锋老师｜北京大学长沙计算与数字经济研究院｜香港理工大学MIND实验室｜香港理工大学李青教授｜大湾区大学杨斯崑老师｜墨尔本大学Ting Dang老师｜南方科技大学荆炳义教授｜香港科技大学（广州）白云老师｜佐治亚大学卢国玉老师｜北京大学孔桂兰老师｜北京大学张辉帅老师｜香港科技大学（广州）王泽宇老师

加入社群 🌟

为了更好地了解和满足大家的需求，我们建立了「求职者社群」。

加入 AI 求职社群，你可以享有招聘需求曝光、获取最新面试经验、校招准备攻略、硕博招生和独家内推渠道等服务。

扫描下方小助手的微信，pick 你心仪的岗位~

如何发布招聘

AI 求职是「PaperWeekly」旗下聚焦人工智能领域的招聘平台，涵盖高校硕博招生、博士后招募、企业校招、社招、实习和内推等。

目前已有百度、阿里、腾讯、字节跳动等企业发布内推岗位，欢迎大家订阅关注、发布岗位，如果你也想对公司和在招职位进行更多曝光，请联系我们的栏目负责人（微信：pwbot02）。

继续阅读

阅读原文