神经形态计算博士职位

PhD position in Neuromorphic Computing, FPGA Design, and Hardware Acceleration

University of Groningen · 荷兰 · Groningen

原帖优先:申请材料、截止时间与资格以原帖和学校官方说明为准。

AI 中文速览

研究内容
设计和开发下一代神经形态计算系统
申请条件
原文未说明
待遇
EUR 3204 - 4051 per month
申请方式
原文未说明
材料清单
  • 原文未说明

由 @cf/meta/llama-3.3-70b-instruct-fp8-fast 生成,博士岗判定置信度 100%。

结构化信息

截止
(Europe/Amsterdam) 剩 23 天
学科
神经科学
合同类型
雇佣合同
原文薪资
EUR 3,204–4,051 / 月(税前)
税后月薪(估)
¥19,000–¥24,000;房租后 ¥11,100–¥16,100
估算假设
单身、无子女、雇佣合同的粗略估算,以学校 offer 为准;扣除率 25%;汇率日期 2026-10-01
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内容更新
来源
AcademicTransfer(荷兰学术招聘) · 最近核对 2026-10-07
判定依据(原文摘录)
  • is_phd
    PhD candidate
  • english_ok
    leading international conferences and journals
原文

Are you excited about designing the next generation of energy-efficient AI hardware? Do you want to contribute to cutting-edge research at the intersection of neuromorphic computing, computer architecture, and hardware acceleration?

The University of Groningen is seeking a highly motivated PhD candidate to join the international QuNeCo project, a collaborative research initiative between leading universities in the Netherlands and Japan. As part of an interdisciplinary team, you will develop novel neuromorphic computing architectures inspired by the human brain to enable future heterogeneous computing systems with unprecedented energy efficiency and performance.

This PhD position offers the opportunity to collaborate with internationally renowned researchers, publish in leading conferences and journals, and gain experience in architecture design, hardware implementation, FPGA prototyping, and AI applications.

What are you going to do?

As a PhD candidate, you will contribute to the design and development of next-generation neuromorphic computing systems through algorithm–hardware co-design and computing-in-memory technologies. Your research will span the complete hardware design flow, from architectural exploration to hardware prototyping and experimental evaluation.

Project website: Home | QuNeCo

Your responsibilities include:

• Designing novel neuromorphic computing architectures based on application requirements and heterogeneous computing use cases.

• Investigating emerging memory technologies, including SRAM, RRAM, MRAM, and FeRAM, for efficient neuromorphic hardware implementations.

• Developing RTL implementations of neuromorphic architectures using hardware description languages and validating their functionality through simulation.

• Evaluating performance, energy efficiency, and scalability using industry-standard electronic design automation (EDA) tools.

• Developing representative AI and neuromorphic applications to demonstrate the proposed architectures.

• Prototyping hardware accelerators on FPGA platforms and integrating them into heterogeneous computing systems.

• Performing comprehensive experimental evaluations and publishing research findings in leading international conferences and journals.

• Collaborating closely with project partners in the Netherlands and Japan and participating in international project meetings, workshops, and research visits.

• Contributing to teaching activities and supervising Bachelor's and Master's students where appropriate.

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