Graybox Tunneling for Multi-Objective Optimization on HPC

Inria, the French national research institute for the digital sciences; France; Sur place; EUR 36 000 - 51 000; Plein temps

Avantages offerts par ce poste

Transport allowance

Teleworking after 6 months

Annual leave 7 weeks + RTT

Training opportunities

Work equipment provided

Résumé du poste

Inria in France seeks a postdoctoral researcher to design, develop and validate graybox tunneling algorithms for multi-objective combinatorial optimization, with emphasis on parallelization and scalability on HPC platforms.

The role focuses on leveraging problem structure to navigate Pareto local optima, extending single-objective tunneling to multi-objective settings, exploring island-model parallelism, and implementing prototypes for large-scale experiments.

Qualifications

• PhD in a relevant field or closely related discipline.
• Strong background in combinatorial optimization.
• Experience with parallel/HPC computing.
• Proven track record of experimental validation on HPC platforms.

Responsabilités

• Design graybox tunneling algorithms for multi-objective optimization.
• Develop parallel tunneling strategies across multiple levels of parallelism.
• Create hybrid island-based optimization approaches.
• Implement and assess scalability of parallel tunneling on HPC platforms.
• Conduct experimental validation and comparative evaluation on MEC problems.

Connaissances

Graybox tunneling

Multi-objective optimization

Parallelization

HPC computing

Combinatorial optimization

Evolutionary computation

Formation

PhD in Computer Science or related field

Outils

C++

Distributed computing

Description du poste

Inria in France seeks a postdoctoral researcher to design, develop and validate graybox tunneling algorithms for multi-objective combinatorial optimization, with emphasis on parallelization and scalability on HPC platforms.

The role focuses on leveraging problem structure to navigate Pareto local optima, extending single-objective tunneling to multi-objective settings, exploring island-model parallelism, and implementing prototypes for large-scale experiments.