Fortran Developer with background in Math
Fortran 90/95Numerical Linear AlgebraCholesky DecompositionLapack
6 дні тому
data_science
L
Luxoft
KyivПро позицію
One of the world's largest providers of products and services to the energy industry has a need to develop and support enterprise information system in Oil & Gas domain. This role focuses on building, integrating, and hardening a Bayesian Optimization (BO)–based engine for optimization in petroleum surface networks.
Обовʼязки6
- Implement and integrate Bayesian Optimization workflows within the existing NEXUS surface network optimization framework
- Develop and maintain Gaussian Process–based surrogate models used during optimization runs
- Integrate acquisition functions that support reliable decision-making across challenging objective landscapes
- Implement initial sampling strategies to ensure stable and repeatable optimization outcomes
- Contribute to performance tuning, memory efficiency, and parallel execution in large simulation workloads
- Improve code robustness, testability, and maintainability in a long-lived product codebase
Вимоги12
- Fortran 90/95
- Experience working with modules, allocatable arrays, and structured Fortran code
- Ability to modify and extend existing numerical code responsibly
- Numerical linear algebra fundamentals
- Practical use of Cholesky decomposition and triangular solves
- Experience using LAPACK routines
- Awareness of numerical stability and basic conditioning issues
- Understanding of Gaussian Process concepts
- Ability to implement or adapt GP prediction code with guidance
- Familiarity with acquisition functions such as Expected Improvement (EI) and Upper Confidence Bound (UCB)
- Understanding of exploration vs. exploitation from a user-outcome perspective
- Experience implementing or using space-filling designs for initial parameter exploration
Fortran Developer with background in Math
Оригінал