Locus Robotics - PhD Research Intern – AI & Computer Vision
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Requirements
• Currently enrolled in a PhD program in Computer Vision, Robotics, Machine Learning, or a closely related field. • Strong foundation in AI, deep learning, and computer vision. • Hands-on experience with PyTorch (preferred) or TensorFlow. • PyTorch • Proficiency in Python; working knowledge of C++ is a plus. • Python • Experience with robot perception systems (e.g., RGB-D cameras, stereo vision, LiDAR). • robot perception systems • Strong analytical and problem-solving skills. • Excellent English communication skills and ability to collaborate in a distributed, multidisciplinary team. • Experience working with large-scale datasets or real-world robotics deployments. • Prior publications in top-tier robotics, CV, or ML venues. • Familiarity with SLAM, visual odometry, or 3D reconstruction pipelines.
Responsibilities
• Develop advanced computer vision algorithms for object recognition, scene understanding, visual SLAM, and 3D perception in real-world robotic environments. • Enhance robotic perception systems supporting navigation, localization, manipulation, and task execution using multimodal sensor data (RGB, depth, LiDAR). • Research and prototype modern AI architectures, including: • State of the Art Visual SLAM and Structure from Motion • Large Language Models (LLMs) for robotics • Generative AI and diffusion models • Neural rendering, radiance fields, and Gaussian splatting • Graph neural networks and self-supervised learning • Deploy and evaluate research at scale, transitioning ideas from prototype to production-ready systems. • Collaborate closely with researchers and engineers across computer vision, robotics, machine learning, and software engineering. • Document and communicate findings through technical reports, internal presentations, and (where appropriate) academic publications.
Benefits
• Unmatched real-world data: Work with data from 15,000+ robots operating across hundreds of customer sites globally. • Real impact: Your work directly influences production robotic systems used daily in live customer environments. • Research meets reality: Bridge cutting-edge academic research with deployment at scale. • World-class mentorship: Learn from experienced researchers and engineers working at the intersection of AI and robotics. • Career pathways: High-performing interns may be considered for future internships, extended research collaborations, or full-time roles. • Research Areas of Interest • We are particularly interested in candidates excited by one or more of the following: • Anomaly Detection • Generative AI & Diffusion Models • Neural Rendering, Radiance Fields, Gaussian Splatting • Robot Localization & Cross-View Geo-Localization • Visual SLAM, Visual Odometry, Structure from Motion • Monocular Depth Estimation & Semantic Segmentation • Birds-Eye View (BEV) Representations • Self-Supervised & Representation Learning • Reinforcement Learning for Robotics • Language Models for Embodied AI
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