Arbetsbeskrivning

Role Description

This is a full-time, on-site position located in Lund for an Algorithms Developer. The role targets a technically strong developer with a solid mathematical foundation who is motivated to transform advanced theory into robust, scalable algorithms for real-world applications. The work focuses on satellite-based measurement systems and large-scale ocean observation, with emphasis on algorithm design, numerical methods, and data-intensive computation.

The successful candidate will drive the development of advanced algorithms for:

• Satellite observation and sensing systems
• Hybrid algorithmic–AI solutions, with attention to stability, robustness, and interpretability
• Large-scale numerical processing of geophysical and oceanographic data
• Fusion and integration of multi-source observational data

Your work will directly contribute to the design and implementation of next-generation surveillance and monitoring systems, influencing both scientific insight and operational performance.

Key Responsibilities

• Design, implement, and optimize algorithms for large-scale scientific and geophysical data analysis
• Develop numerically stable and computationally efficient methods for satellite data processing
• Translate mathematical models into production-quality software and prototypes
• Contribute to algorithmic approaches for multi-source data fusion and inverse problems
• Collaborate closely with mathematicians, physicists, and domain experts in an industrial research environment
• Supervise or mentor Master’s students working on algorithmic or computational research projects

Qualifications

Essential

• PhD (or equivalent research experience) in Mathematics, Computer Science, Engineering, or a closely related field
• Strong background in:
• Algorithm design and analysis
• Numerical methods and scientific computing
• Mathematical modelling (e.g. PDE-based or physics-informed models)
• Proven experience with Python for algorithm development, prototyping, and numerical computation
• Demonstrated track record of research or advanced development output (publications, algorithms, software libraries, or open-source contributions)

Desirable

• Experience with C++, performance-critical code, or high-performance computing
• Familiarity with GPU acceleration or parallel computing frameworks
• Experience working with inverse problems, data assimilation, or sensor fusion
• Exposure to applying machine learning within mathematically grounded algorithmic pipelines