Job Description
Develop and implement algorithms for multi-sensor data fusion (Track-level / Sensor-level Fusion).
Process sensor data, including noise filtering and time synchronization.
Implement and enhance advanced filtering techniques such as Kalman Filters.
Build and evaluate statistical sensor models across various coordinate systems (WGS-84, UTM, ECEF, etc.).
Develop BIAS estimation algorithms for active and passive sensors (e.g., Radar, SIGINT).
Integrate and deploy algorithms into Real-Time / Near Real-Time systems.
Participate in field and laboratory tests, analyze performance, and produce technical reports.
Mandatory Requirements
B.Sc. / M.Sc. in Computer Science, Physics, Mathematics, or a related field.
At least 3 years of industry experience in data fusion and/or target tracking algorithm development.
Strong knowledge of filtering techniques and Data Association / Fusion methods.
Hands-on experience with C++ / Java / C# and Python / MATLAB.
Ability to integrate into complex, multi-layered existing systems.
High self-learning capability.
Strong sense of ownership and responsibility.
Good technical documentation and writing skills in English.
Availability for a position requiring approximately 25-30 overtime hours per month.
Team player with excellent interpersonal skills.
Significant Advantages:
Familiarity with:
Radar / EO / IR systems.
ADS-B / AIS / IFF systems.
Experience with CUDA/GPU acceleration.
Experience working with real-world noisy sensor data.
Experience optimizing code for real-time performance.
