KraviAnalytics AB

Industrial Postdoctoral Researcher in Mathematical Analysis

OmrådeLund
Publicerad2026-01-05
Ansök senast2026-01-13

Om jobbet

Role Description

This is a full-time on-site role located in Lund for an Industrial Postdoctoral Researcher in Mathematical analysis. This Industrial Postdoctoral position is designed for a researcher with a deep, rigorous mathematical background who seeks to apply advanced theory to real-world challenges. The role centres on the mathematical foundations of satellite-based measurement and large-scale ocean observation, with a strong focus on analytical and numerical research.

The successful candidate will lead mathematically driven investigations involving:

Mathematical analysis of satellite observation systems.

Development of hybrid mathematical-AI models, with emphasis on underlying analytical structure and stability

Design, analysis, and implementation of numerical and computational methods for large-scale geophysical and oceanographic data

Mathematical modelling and interpretation of multi-source observational systems

Your mathematical research will directly contribute to the conceptual design of next-generation surveillance systems and influence both scientific understanding and operational capabilities.

Key Responsibilities

Conduct independent and collaborative research in mathematics, including PDEs, mathematical modelling, functional/harmonic analysis, or theoretical/mathematical physics

Develop:

Mathematically well-founded algorithms

Methods for multi-source satellite data fusion

Supervise Master's students in mathematically focused research projects

Qualifications

Essential

PhD in Mathematics

Strong background in:

Partial Differential Equations

Algorithms Development

Functional or Harmonic Analysis

Theoretical Physics / Mathematical Modelling

Proven experience using Python for scientific and numerical computing

Evidence of mathematical research output (publications, preprints, algorithms, or open-source contributions)

Desirable

Experience with C++, GPU acceleration, or high-performance computing.

Familiarity with inverse problems.

KraviAnalytics AB

FöretagKraviAnalytics AB