Research Scientist – Brain-Inspired AI Systems (Contractor)

Company: Huawei Technologies Research & Development (UK) Ltd
Apply for the Research Scientist – Brain-Inspired AI Systems (Contractor)
Location: London
Job Description:

Overview

We are seeking two exceptional Research Scientists to join our innovative project on advancing large language model (LLM) capabilities through brain-inspired approaches. This role will focus on developing novel multi-modal AI architectures that leverage recent insights from neuroscience, specifically working on next-generation memory systems for transformers. The successful candidates will contribute to groundbreaking research in memory compression, hierarchical retrieval, and efficient information processing for next-generation agenting LLMs.

Key Responsibilities

  • Design and implement novel memory algorithms for LLMs.
  • Develop biologically-inspired approaches to improve AI system performance.
  • Research efficient methods for information storage and retrieval in neural networks.
  • Collaborate with world-leading academic experts in computational neuroscience and memory systems.
  • Work closely with the engineering team to optimize implementations for practical deployment.
  • Publish research findings in top-tier conferences and journals.
  • Contribute to patent applications and technical documentation.
  • Work closely with international teams across Huawei’s research centers.

Qualifications

Required:

  • PhD in Computer Science, Neuroscience, Mathematics, or related field (or equivalent industry experience).
  • Strong programming skills in Python.
  • Experience with deep learning frameworks (ideally PyTorch).
  • Good understanding of transformer architectures and attention mechanisms.
  • Background in machine learning or computational neuroscience.

Desired:

  • Good publication record in machine learning or computational neuroscience.
  • Experience with LLMs.
  • Experience with biological learning systems and memory models.
  • Knowledge of Modern Hopfield Networks and associative memory systems.
  • Background in variational inference and/or predictive coding.
  • Understanding of hardware acceleration techniques.

Employment Type

  • Full-time

Industry

  • Telecommunications

#J-18808-Ljbffr…

Posted: July 2nd, 2026