Ai Research Manager

Description:

Responsibilities:

• Innovate Protection Strategies: Analyze signals / time-series for differentiation between inrush and short-circuit events.
• Tailored Protection Design: Utilize signal processing and optimization skills to craft protection functions for individual devices.
• AI-Powered Policies: Employ machine learning, deep learning, and reinforcement learning to formulate circuit breaker protection policies.
• Drive Collaboration: Work with domain experts to translate requirements into effective protection policies, ensuring robustness.
• Enhanced Transparency: Lead the use of techniques like SHAP analysis to enhance model transparency and interpretability.
• Comprehensive Documentation: Document research methodologies and their findings to create technical reports and documentation.

Qualifications:

• Education: Ph.D. or Master's degree in Electrical Engineering, Computer Science, Mechatronics, or related fields with a focus on AI/ML.
• Expertise: Extensive experience in time-series analysis, signal processing, machine learning, deep learning, and reinforcement learning.
• Research Excellence: Demonstrated research in AI/ML through top-tier conference publications (NeurIPS, ICML, etc.) and GitHub contributions.
• Model Proficiency: Mastery of classical and deep machine learning algorithms, reinforcement learning, and optimization techniques.
• Architecture Skills: Proven ability to implement Convolutional, Recurrent, Variational, Generative, and Transformer architectures.
• Unsupervised Learning: Experience in Unsupervised, Semi-Supervised, and Self-Supervised Deep Learning.
• Deep Architectures: Experience in Variational, Adversarial, Flows-based, and Diffusion Generative Model Architectures.
• Electrical Engineering: Knowledge of circuit protection devices and electrical engineering concepts is advantageous.
• Optimization Knowledge: Knowledge in Gradient-based and Blackbox Optimization, incl. Meta-Learning and Evolutionary methods.