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Machine Learning and State Estimation Internship

Harmattan AILausanne
On-site Internship

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Experience Level

Entry Level

Qualifications

Candidate RequirementsCurrently pursuing or recently completed a degree in Computer Science, Engineering, or a related field. Familiarity with machine learning frameworks and programming languages (Python, TensorFlow, etc.). Understanding of state estimation and sensor fusion concepts is a plus. Strong analytical skills and a problem-solving mindset. Excellent communication and teamwork abilities.

About the job

About Us

Harmattan AI is pioneering the development of autonomous and scalable defense systems. Following our successful $200 million Series B funding round, which has resulted in a valuation of $1.4 billion, we are actively expanding our teams to deliver mission-critical systems to allied forces across the globe.

Guided by our core values, we aim to create technologies that have a tangible impact, pursue excellence in all endeavors, set ambitious goals, and tackle the most challenging technical issues. Our environment is demanding, where rigor, ownership, and execution are paramount.

About the Role

As we develop sophisticated autonomous systems, we rely on robust state estimation and sensor fusion to navigate complex and dynamic environments. Our platforms integrate various sensors, including IMU, GNSS, vision, barometer, and magnetometer, necessitating precise, real-time estimation of system states such as position, velocity, and attitude.

While classical methods like Kalman filtering are effective, they often depend on modeling assumptions that may not hold in real-world scenarios. To enhance performance, we are investigating hybrid methodologies that merge model-based estimation and control with cutting-edge machine learning techniques.

Your Mission

In this internship, your objective will be to investigate and implement machine learning-based sensor fusion and state estimation techniques to boost performance in dynamic settings.

Responsibilities

  • Literature Review: Conduct an extensive review of current machine learning methods for state estimation and sensor fusion.

  • Algorithm Implementation: Develop and implement various algorithms informed by your literature review and project specifications using both simulated and real-world flight data.

  • Performance Evaluation: Evaluate and compare the performance and computational demands of the developed algorithms against classical benchmarks.

  • Documentation: Thoroughly document all undertaken work, encompassing methodologies, results, and conclusions.

  • Flight Tests Participation: Engage actively in flight test sessions to collect real-world data and validate the efficacy of the developed algorithms under operational conditions, contributing to real-time deployment.

About Harmattan AI

Harmattan AI is at the forefront of innovation in autonomous defense systems, focusing on scalable solutions that meet the needs of allied forces. With significant funding and a commitment to excellence, we strive to make a meaningful impact through advanced technology.

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