Application Open:
Full-Time
Job Purpose:
MBZUAI is seeking an engineer to lead the development of cutting-edge AI systems that decode human neural intent into natural humanoid robot behavior. You will create AI models that learn individual neural patterns and enable seamless translation of thoughts into sophisticated robotic policies and actions, revolutionizing assistive technology for individuals with paralysis.
Key Responsibilities:
Neural Decoding AI Model Development:
- Design and implement deep learning architectures for decoding movement intentions from invasive neural signals.
- Develop continuous control models that extract desired humanoid robot policies and action commands.
- Create personalized models that adapt to individual neural signatures and improve over time.
- Build ensemble methods that combine multiple decoding approaches for robust performance.
Multimodal AI Integration:
- Develop fusion models that integrate brain signals, EMG, eye-tracking, motion capture, and force sensor data.
- Create temporal models that predict movement intentions before explicit neural commands.
- Design attention mechanisms that dynamically weight different sensory modalities.
- Implement transfer learning approaches to generalize across patients and sessions.
Human Intent Recognition:
- Build classification systems that recognize high-level intentions for humanoid robot control.
- Develop policy prediction models that anticipate desired robot behaviors and skills.
- Create context-aware systems that understand task goals and environmental constraints.
- Design confidence estimation frameworks that quantify decoder certainty.
Real-Time Deployment & Optimization:
- Optimize AI models for real-time inference with minimal latency requirements.
- Develop online learning systems that continuously adapt to changing neural patterns.
- Create efficient model architectures suitable for embedded robotics hardware.
- Implement model validation and performance monitoring systems.
Project Statistics & Reporting:
- Monitor and evaluate project milestones and deliverables, ensuring accurate tracking of task completion and adherence to timelines.
- Compile and present concise reports and performance dashboards for management and stakeholders, highlighting progress, risks, and outcomes.
- Generate actionable insights from project data to optimize execution, resource utilization, and overall research effectiveness.
Other Duties:
- Perform all other duties as reasonably directed by the line manager that are commensurate with these functional objectives.
Academic Qualification:
- Bachelor degree in Computer Science, Electrical Engineering, or a related field.
- A postgraduate degree will be strongly preferred.
Professional Experience:
Essential
- Minimum 2 years of experience with machine learning and deep learning frameworks (PyTorch, TensorFlow) or a related technical field.
- Strong programming skills in Python with scientific computing libraries.
- Experience with time-series analysis and sequential data processing.
- Knowledge of signal processing and feature extraction techniques.
- Experience deploying models for real-time applications.
Preferred
- Experience with biomedical signal processing or brain-computer interfaces.
- Background in reinforcement learning and control applications.
- Knowledge of embedded systems and optimization for real-time performance.
- Experience with multimodal data fusion.
- Familiarity with ROS and robotics software development.
- Working proficiency in additional languages is an advantage.
