Experience:

• 10–12+ years of research or industry experience focused on advanced mathematical modeling, machine learning, and algorithm design

Qualification:

• PhD in Applied Mathematics, Computer Science, Operations Research, Statistics, Electrical Engineering, or a closely related discipline

Responsibilities:

• Complex Systems Modeling: Design data-driven and algorithmic models that capture the complex behavior of decentralized physical assets
• Agent-Based & Behavioral AI: Develop reinforcement learning and multi-agent frameworks
• Economic & Incentive Design: Help design algorithmic 'rules of the game'
• Optimization Under Uncertainty: Build robust optimization models
• Physics-Aware AI: Collaborate with engineering teams to embed strict physical safety limits
• Thought Leadership: Drive the research agenda for the division

Nice to have:

• Domain Exposure: Prior exposure to energy systems, smart grids, algorithmic trading, or complex supply chain networks
• Research Pedigree: A track record of publishing impactful research in top-tier AI/ML venues
• Cross-Disciplinary Collaboration: Proven ability to translate abstract mathematical concepts into practical tools

More skills:

deep learning frameworks (PyTorch, JAX, or TensorFlow), mathematical solvers (e.g., Gurobi, SCIP, CVXPY), Behavioral Economics, Physics-Informed Machine Learning (PINNs)