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Master Thesis in Large-Scale Optimization for Supply Chain Logistics(m/w/x)
Developing modular optimization framework for real-world Inventory Routing Problem. Knowledge in combinatorial optimization required; experience with optimization or ML libraries a plus. Workplace in new institute building, flexible working style.
Requirements
- Programming skills (preferably Python) and good software engineering practices
- Linux OS and Git-based version control
- Knowledge in combinatorial optimization
- Experience in implementing machine learning solutions (reinforcement learning)
- Experience with optimization libraries (Gurobi, CPLEX, HiGHS), machine learning libraries (pytorch, tensorflow), or real-world data handling (plus)
- Enrollment in a German university (preferably Munich or surrounding area)
- Suitability for M.Sc. Computer Science, Cognition, Intelligence, Data Engineering, Mathematics, or related subjects
Tasks
- Develop a modular optimization framework for a real-world Inventory Routing Problem
- Review relevant literature
- Review existing solution approaches
- Formalize the use case
- Define problem scale and constraints
- Formalize available data
- Design a prototypical end-to-end system
- Implement a prototypical end-to-end system
- Research temporal, spatial, and mathematical decomposition strategies
- Implement a modular solution using optimization, quantum, or AI techniques
- Orchestrate the full solution
Education
- Currently in higher education
Languages
- English – Business Fluent
Tools & Technologies
- Python
- Linux OS
- Git
- Gurobi
- CPLEX
- HiGHS
- pytorch
- tensorflow
Benefits
Flexible Working
- Flexible working style
Modern Office
- Workplace in new institute building
Informal Culture
- Approachable supervisors
- Integration into dynamic team
Diverse Work
- Innovative task areas
Purpose-Driven Work
- Insights into applied science practices
Other Benefits
- Practical approach to studies
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Master Thesis in Large-Scale Optimization for Supply Chain Logistics(m/w/x)
Developing modular optimization framework for real-world Inventory Routing Problem. Knowledge in combinatorial optimization required; experience with optimization or ML libraries a plus. Workplace in new institute building, flexible working style.
Requirements
- Programming skills (preferably Python) and good software engineering practices
- Linux OS and Git-based version control
- Knowledge in combinatorial optimization
- Experience in implementing machine learning solutions (reinforcement learning)
- Experience with optimization libraries (Gurobi, CPLEX, HiGHS), machine learning libraries (pytorch, tensorflow), or real-world data handling (plus)
- Enrollment in a German university (preferably Munich or surrounding area)
- Suitability for M.Sc. Computer Science, Cognition, Intelligence, Data Engineering, Mathematics, or related subjects
Tasks
- Develop a modular optimization framework for a real-world Inventory Routing Problem
- Review relevant literature
- Review existing solution approaches
- Formalize the use case
- Define problem scale and constraints
- Formalize available data
- Design a prototypical end-to-end system
- Implement a prototypical end-to-end system
- Research temporal, spatial, and mathematical decomposition strategies
- Implement a modular solution using optimization, quantum, or AI techniques
- Orchestrate the full solution
Education
- Currently in higher education
Languages
- English – Business Fluent
Tools & Technologies
- Python
- Linux OS
- Git
- Gurobi
- CPLEX
- HiGHS
- pytorch
- tensorflow
Benefits
Flexible Working
- Flexible working style
Modern Office
- Workplace in new institute building
Informal Culture
- Approachable supervisors
- Integration into dynamic team
Diverse Work
- Innovative task areas
Purpose-Driven Work
- Insights into applied science practices
Other Benefits
- Practical approach to studies
About the Company
Fraunhofer Institute for Cognitive Systems IKS
Industry
Research
Description
The company conducts research on reliable and safe applications of cognitive systems, including AI and quantum computing.
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