Inactive
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Locus Robotics

Autonomous mobile robots for warehouse automation

PhD Research Intern - AI & Computer Vision

Computer VisionPosted on Apr 8
Internship · Summer 2026Remote in UKNo salary listedRemote

About the Job

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.
  • Proficiency in Python; working knowledge of C++ is a plus.
  • Experience with robot perception systems (e.g., RGB-D cameras, stereo vision, LiDAR).
  • 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 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.

Desired Qualifications

  • 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

About the Company

Locus Robotics

Autonomous mobile robots for warehouse automation

Locus Robotics provides warehouse automation using Autonomous Mobile Robots (AMRs) to improve efficiency and lower labor costs. Their system works by deploying AMRs that handle tasks such as picking, putaway, transport, and mezzanine management, all coordinated through the LocusOne data science–driven platform. The robots operate on a Robots as a Service (RaaS) model, meaning customers pay a subscription for both the robots and the software, enabling rapid deployment and scalable growth without large up-front investments. What sets Locus Robotics apart is its combination of an enterprise-wide AMR deployment platform, strong data analytics and visibility tools, and a focus on security and data privacy, allowing businesses to monitor performance and continuously optimize workflows. The company’s goal is to help enterprises in logistics and e-commerce fulfill orders faster and more reliably while reducing operating costs through scalable, data-backed automation.

Company size
201-500
Company stage
Series G
Total funding
$457.6M
Headquarters
Wilmington, MA
Founded
2014

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