Research Scientist

We are looking for a Research Scientist – Advanced Optimization Specialist with a strong mathematical and computational background to tackle a challenging optimization problem involving fast, multidimensional parameter searches. The ideal candidate will be deeply familiar with algorithmic optimization, statistical modeling, and machine learning techniques, focusing on developing efficient solutions for complex, high-dimensional spaces.Key Responsibilities:Develop and Implement Optimization Algorithms: Design advanced optimization algorithms (e.g., Bayesian optimization, surrogate modeling, multi-fidelity methods) for fast convergence in high-dimensional parameter spaces.Research and Experimentation: Conduct research to identify and validate effective optimization techniques, balancing speed and accuracy.Mathematical and Statistical Modeling: Use mathematical modeling and statistical methods to improve optimization efficiency.Machine Learning Integration: Apply machine learning models (e.g., Gaussian Processes, Random Forests) to enhance the optimization process.Collaborate and Integrate: Work closely with developers to integrate optimization solutions into existing computational frameworks.Analyze and Refine: Continuously evaluate and refine algorithms based on performance data.Qualifications:MA in Mathematics, Computer Science, Statistics, or Related FieldExpertise in Optimization Algorithms: Experience with techniques such as Bayesian optimization, Evolutionary Algorithms, and multi-fidelity methods.Strong Analytical Skills: Proficiency in mathematical modeling and solving complex optimization problems.Machine Learning Knowledge: Familiarity with machine learning methods applied to optimization.Programming Skills: Proficiency in Python and related scientific computing libraries (e.g., NumPy, SciPy, scikit-learn). #J-18808-Ljbffr