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As a member of our R&D teams, you will apply your digital skills in the field of operations research to design and develop cutting-edge optimization solvers. You will often have the opportunity to work on various types of digital libraries developed by Artelys: continuous and mixed nonlinear programming (Artelys Knitro), constraint programming (Artelys Kalis), optimization of energy systems (Artelys Crystal Optimization Engine). You will be responsible for developing new algorithmic features combining mathematics and computer science, while striving to maintain a high level of software robustness and performance.
Job Responsibility:
Apply digital skills in the field of operations research to design and develop cutting-edge optimization solvers
work on various types of digital libraries developed by Artelys
develop new algorithmic features combining mathematics and computer science
maintain a high level of software robustness and performance
develop solutions for numerical and combinatorial optimization software, computation modules for clients, or prototypes within research projects
Requirements:
Holder of a PhD in applied mathematics or operations research, or have equivalent experience of at least 3 years after obtaining an engineering degree or higher education qualification
proficiency in Python or C/C++ programming language
expertise in various optimization methods: graph theory, continuous optimization algorithms, combinatorial optimization algorithms, nonlinear optimization, etc.
proficiency in designing and optimizing algorithms for high performance computing (HPC) environments
fluency in English
Nice to have:
French is a plus
additional knowledge in software programming (Spring, BDD, NoSQL, REST/Microservices, Message queuing, etc.) and in compilation
proficient in other programming languages (MATLAB, R, Julia, Java, C#)
proficient in linear algebra tools (especially methods for solving linear systems)
previous contributions to open source projects related to numerical optimization, simulation, or computational science
active participation in relevant communities and networks
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