Master's/PhD Research Fellow – Operations Researcher, ATM Cash Inventory Optimization
Job not on LinkedIn
🔥 0 minutes ago
🗣️🇧🇷🇵🇹 Portuguese Required
📊 Check your resume score for this job
Improve your chances of getting an interview by checking your resume score before you apply.
📋 Description
• 12-month project to develop and compare approaches for optimizing cash denomination provisioning per withdrawal at ATM terminals • Formalization of the problem (variables, physical constraints, objective function) and a simulation environment using withdrawal history and Monte Carlo resampling • Development and comparison of three approaches — periodic offline policy; predict-then-optimize combined with reinforcement learning; short-horizon online MIP with a fallback • Coordination at the battery level (a set of terminals) to align depletion and reduce aggregated restocking • Evaluation against baselines (largest-denomination, proportional, threshold) using metrics for restocking events, time between restocks, service rate, latency, and traceability
🎯 Requirements
• PhD or Master's degree • Currently enrolled in or completed studies in Computer Engineering, Computer Science, Electronic Engineering, Applied Mathematics, or Statistics • Experience using solvers (CPLEX, Gurobi, CBC, HiGHS, etc.) • Mathematical modeling techniques using Operations Research (linear programming, mixed-integer programming, heuristics, etc.) • Programming experience in Python
🏖️ Benefits
• Monthly stipend: R$ 9,000 (Master's) and R$ 11,000 (PhD) • Work arrangement: Remote
Apply NowSimilar Jobs
🕒 May 21
Research Scientist designing benchmarks and evaluations for AI training data. Working on key evaluation datasets to enhance scientific rigor and industry standards.
🕒 May 6
Senior Researcher leading evaluations and optimizations of video datasets for generative AI models at Protege. Focused on ensuring video data quality and impact for model training.
🕒 April 20
avra
1 - 10
Research Scientist defining and executing AI research agenda with global advisers. Building ML pipelines and innovative solutions in a fully remote position.
