Remote-friendly Radar AI & Deep Learning Intern

robin-radar; Netherlands; Hybrid; EUR 6,700 - 10,000; Full time

Benefits offered by this job

Commuting allowance

High quality equipment

Work from home option

Internship stipend €500/€750 per month

Great Place to Work certification

International team of 30+ nationalites

Job summary

Robin is expanding its AI team and seeks an AI & Deep Learning Intern to advance radar tracking and classification research in real time. You will own a high-impact research track, from literature review through implementation and evaluation, within our hybrid work setup in the Netherlands.

You will adapt deep learning methods in Python/PyTorch, develop metrics for uncertainty estimates and classification accuracy, and deliver a documented software framework along with a comparative study.

Qualifications

• Proficiency in Python and hands-on experience with deep learning frameworks, specifically PyTorch.
• Strong understanding of neural network architectures (e.g., ResNet) and general deep learning concepts.
• Excellent written and verbal communication skills in English.

Responsibilities

• Investigate state-of-the-art techniques relevant to your chosen research track (Radar Track Clustering, Contrastive Features, Input Channel Adaptation Layer, Position Estimation).
• Adapt and implement deep learning strategies into our existing Python/PyTorch frameworks.
• Develop metrics and evaluate the quality of uncertainty estimates or classification accuracy.
• Investigate how your research improves downstream radar tasks, such as risk-aware decision-making or real-time drone detection.
• Deliver a documented software framework and a comparative study of methods.

Skills

Python

PyTorch

ResNet

Deep learning concepts

Education

MSc in AI/Computer Science/Physics

Job description

Robin is expanding its AI team and seeks an AI & Deep Learning Intern to advance radar tracking and classification research in real time. You will own a high-impact research track, from literature review through implementation and evaluation, within our hybrid work setup in the Netherlands.

You will adapt deep learning methods in Python/PyTorch, develop metrics for uncertainty estimates and classification accuracy, and deliver a documented software framework along with a comparative study.