阿里巴巴达摩院-AIGC算法工程师-医疗影像生成方向
社招全职1年以上技术类-算法地点:北京 | 杭州状态:招聘
工作描述
任职要求 1. 计算机科学、人工智能、电子工程、生物医学工程等相关专业的硕士或博士毕业,在视觉生成或者医疗影像AI上有实际的研发经历,精通深度学习、机器学习、计算机视觉及医学影像处理,工业界相关研发工作经验不少于一年。 2. 熟悉扩散模型、Controlnet、影像增强、自回归生成等主流视觉AIGC算法,有实际的影像生成相关的应用落地经验。 3. 熟悉医疗影像数据,能够根据不同医学影像特性进行数据处理和算法设计,或者对于医疗AI有强烈兴趣。 4. 熟悉主流深度学习框架(如PyTorch、TensorFlow),并具备Transformer、CNN等典型深度学习模型的原理及实现经验。熟练掌握编程语言(如Python、C++等),并熟悉LINUX环境的开发与调试。 5. 具备出色的团队协作精神和沟通能力,自我驱动,抗压能力强,拥有强烈的求知欲和对技术的热情,良好的数据和逻辑分析能力。 加分项: 1. 具备良好的科研能力,曾在国际顶级会议和期刊(如ICLR、ICCV、CVPR、ECCV、NeurIPS、ICML、MICCAI、…
登录查看完整工作描述
微信扫码,1秒登录
包括英文材料
深度学习+
https://d2l.ai/
Interactive deep learning book with code, math, and discussions.
机器学习+
https://www.youtube.com/watch?v=0oyDqO8PjIg
Learn about machine learning and AI with this comprehensive 11-hour course from @LunarTech_ai.
https://www.youtube.com/watch?v=i_LwzRVP7bg
Learn Machine Learning in a way that is accessible to absolute beginners.
https://www.youtube.com/watch?v=NWONeJKn6kc
Learn the theory and practical application of machine learning concepts in this comprehensive course for beginners.
https://www.youtube.com/watch?v=PcbuKRNtCUc
Learn about all the most important concepts and terms related to machine learning and AI.
OpenCV+
https://learnopencv.com/getting-started-with-opencv/
At LearnOpenCV we are on a mission to educate the global workforce in computer vision and AI.
https://opencv.org/university/free-opencv-course/
This free OpenCV course will teach you how to manipulate images and videos, and detect objects and faces, among other exciting topics in just about 3 hours.
AIGC+
https://ui.adsabs.harvard.edu/abs/2023arXiv230406632W/abstract
To address the challenges of digital intelligence in the digital economy, artificial intelligence-generated content (AIGC) has emerged.
算法+
https://roadmap.sh/datastructures-and-algorithms
Step by step guide to learn Data Structures and Algorithms in 2025
https://www.hellointerview.com/learn/code
A visual guide to the most important patterns and approaches for the coding interview.
https://www.w3schools.com/dsa/
PyTorch+
https://datawhalechina.github.io/thorough-pytorch/
PyTorch是利用深度学习进行数据科学研究的重要工具,在灵活性、可读性和性能上都具备相当的优势,近年来已成为学术界实现深度学习算法最常用的框架。
https://www.youtube.com/watch?v=V_xro1bcAuA
Learn PyTorch for deep learning in this comprehensive course for beginners. PyTorch is a machine learning framework written in Python.
TensorFlow+
https://www.youtube.com/watch?v=tpCFfeUEGs8
Ready to learn the fundamentals of TensorFlow and deep learning with Python? Well, you’ve come to the right place.
https://www.youtube.com/watch?v=ZUKz4125WNI
This part continues right where part one left off so get that Google Colab window open and get ready to write plenty more TensorFlow code.
Transformer+
https://huggingface.co/learn/llm-course/en/chapter1/4
Breaking down how Large Language Models work, visualizing how data flows through.
https://poloclub.github.io/transformer-explainer/
An interactive visualization tool showing you how transformer models work in large language models (LLM) like GPT.
https://www.youtube.com/watch?v=wjZofJX0v4M
Breaking down how Large Language Models work, visualizing how data flows through.
CNN+
https://learnopencv.com/understanding-convolutional-neural-networks-cnn/
Convolutional Neural Network (CNN) forms the basis of computer vision and image processing.
[英文] CNN Explainer
https://poloclub.github.io/cnn-explainer/
Learn Convolutional Neural Network (CNN) in your browser!
https://www.deeplearningbook.org/contents/convnets.html
Convolutional networks(LeCun, 1989), also known as convolutional neuralnetworks, or CNNs, are a specialized kind of neural network for processing data.
https://www.youtube.com/watch?v=2xqkSUhmmXU
MIT Introduction to Deep Learning 6.S191: Lecture 3 Convolutional Neural Networks for Computer Vision
还有更多 •••
相关职位

社招1年以上技术类-算法
1. 计算机科学、人工智能、电子工程、生物医学工程等相关专业的硕士或博士毕业,在视觉生成或者医疗影像AI上有实际的研发经历,精通深度学习、机器学习、计算机视觉及医学影像处理,工业界相关研发工作经验不少
更新于 2026-04-01北京|杭州

社招10年以上
- 本科及以上,电子/通信/计算机/微电子等相关专业,3 年以上云计算服务平台交换/网络芯片产品经理经验。 - 深度理解云计算服务平台网络架构,精通 Scale-Up 多芯片互联、组网技术,熟悉业内超
更新于 2026-06-17北京|杭州|上海
社招5年以上技术类-开发
1. 教育背景 - 计算机科学、人工智能、数据科学或相关领域的本科及以上学历。 2. 专业技能 - AI理论基础:深厚的AI理论基础,熟悉机器学习、深度学习、自然语言处理等领域的新技术和研究进展。 -
更新于 2026-07-17上海