工作年限:
五年以上

所属部门:
阿里集团

学 历:
博士

招聘人数:
若干

团队介绍:
The Computing Technology Lab focuses on advanced research topics in computing, memory/storage, and interconnect technologies that can revolutionize today's computing systems with holistic innovations ranging from system architectures to VLSI designs, to enable new computing capabilities for improving energy efficiency and performance across multiple application domains, including both high-performance and embedded computing.
Therefore you will have excellent work opportunities with field leading experts from all different domains to change the world. And also we rapidly advance team members who have an outsized impact.

岗位描述:
Alibaba DAMO academy Computing Technology Lab (CTL) is seeking leading neuromorphic computing hardware research scientists who can think out of box. The developed neuromorphic software-hardware products will be served for academic research and computing requirement from Alibaba corresponding business units in the long-run.

Our vision is to investigate the Spiking Neural Network (SNN) architecture for general artificial intelligence with strong fault tolerance, ultra-low power consumption, and on-chip self-learning capability, which make strong real-world impacts and profits for Alibaba. As hardware architecture research scientists in our lab, the key responsibilities will be as followed:

• You will be responsible for developing novel neuromorphic hardware architecture which can smartly implemented developed algorithms, and also serve as a platform to help software team to explore SNN compatible algorithms.
• You will work closely with and give strong support to neuromorphic software/algorithm researchers. You will give clear directions of the hardware development roadmap and meet the requirements from Alibaba business units.
• You will publish on field leading journals and conferences.
• You will constantly generate and apply new patents for Alibaba neuromorphic computing products, and to build a technical barrier for Alibaba.

岗位要求:

• Ph.D. in Computer Science, Microelectronic/Computer Engineering, or a related field.
• Strong neuromorphic hardware architecture design experiences on FPGA/ASIC and industry/postdoc related research experiences.
• Solid neuromorphic training/computing algorithm comprehension.
• Field-leading publications to demonstrate the work abilities and research qualities.
• Experiences on developing neuromorphic computing-based applications (e.g. neural modelling, image/video processing, neuroprosthesis) is strongly preferred.
• Strong self-motivations, team work spirits and communication skills, willing work hard and achieve something.