Mathematical Algorithm Engineer – m/f/d

🔥 7 minutes ago

🇩🇪 Germany – Remote

⏳ Contract/Temporary

🟡 Mid-level

🟠 Senior

👷🏻‍♀️ Engineer

👻 Ghost score 18%

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Capgemini

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1967

💼 Consulting

🏥 Healthcare

📦 Logistics

Consulting • Healthcare • Logistics

Capgemini is a global leader in partnering with businesses to transform and manage their operations by harnessing the power of technology. With expertise across a wide array of industries such as aerospace, automotive, banking, and healthcare, Capgemini provides a constantly evolving portfolio of services to meet the ever-changing needs of their clients. Their offerings include cloud, cybersecurity, data and artificial intelligence, and enterprise management, among others. Capgemini also emphasizes innovation and sustainability, helping companies achieve digital transformation while promoting environmental and social responsibility. Additionally, Capgemini provides career opportunities across various levels and professions, encouraging innovation and diversity in its workforce.

📋 Description

• Develop mathematical models, calibration algorithms, and numerical solution methods for complex optical measurement and inspection systems • Formulate and solve optimization, estimation, and inverse problems while taking accuracy, stability, and numerical robustness into account • Implement, test, and optimize algorithms in C++ and Python • Ensure performance, convergence, and quality requirements are met • Analyze measurement data and conduct sensitivity and uncertainty analyses • Validate simulation results against real experimental data from laboratory environments • Document mathematical models, solution approaches, and results in technical specifications, white papers, and development documentation

🎯 Requirements

• Completed degree in mathematics, physics, computer science, computational science, electrical engineering, or a comparable field • Relevant professional experience in developing, implementing, and validating mathematical algorithms in a scientific or industrial environment • Excellent knowledge of numerical linear algebra • Excellent knowledge of numerical optimization methods • Excellent knowledge of statistical estimation theory • Excellent knowledge of Bayesian modeling • Excellent skills in developing and implementing mathematical algorithms with C++ and Python • Knowledge of NumPy and SciPy is an advantage • Experience with numerical simulations, inverse problems, signal processing, or computational imaging is an advantage • Fluent written and spoken German and English

🏖️ Benefits

• Specialized training • Mentoring • Innovative projects • Location-flexible work depending on project requirements and team coordination • Flexible working hours • Work across multiple locations • Work in a diverse and open team • Broad range of learning opportunities for professional and personal development • Temporary assignment to a customer project

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