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• 12-month project to unify Treasury, Shipments and ATM models into a single MIP solution • Assessment of the three models (variables, constraints, interfaces) and historical analysis of instability and misalignments • Unified MIP formulation with coupling constraints across layers • Testing decompositions (Benders, Lagrangian, Dantzig–Wolfe) on increasing instance sizes • Warm-start heuristics (relax-and-fix, fix-and-optimize) to accelerate the solver • Integration of the data pipeline, execution on geographic segments and scaling to national level • Backtesting with 3 months of real data, comparing against baselines and evaluating cost, stability, adherence and runtime • Delivery of a functional prototype, technical documentation and recommendations for phased deployment
• PhD or Master’s degree • Currently enrolled in or graduated in Computer Engineering, Computer Science, Electronic Engineering, Applied Mathematics or Statistics • Mathematical modeling techniques using Operations Research (linear programming, mixed-integer programming, heuristics, etc.) • Experience using solvers (CPLEX, Gurobi, CBC, HiGHS, etc.) • Programming in Python • Desirable: Optimization software (FICO Xpress, AIMMS, others), R, SQL, AWS Cloud, Agile methodology (Scrum), experience with end-to-end projects
• Stipend: Master’s BRL 9,000; PhD BRL 11,000 • Availability: 40 hours per week
Apply Now🕒 May 21
Research Scientist designing benchmarks and evaluations for AI training data. Working on key evaluation datasets to enhance scientific rigor and industry standards.
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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.
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Research Scientist defining and executing AI research agenda with global advisers. Building ML pipelines and innovative solutions in a fully remote position.