Computer Vision Researcher

18 ore fa

Rome, Italia microTECH Global LTD A tempo pieno

Computer Scientists – Deep Learning for 3D Reconstruction in Sustainable Agriculture An innovative research organization is seeking two skilled Computer Scientists to join its applied research team focused on advancing sustainable agriculture through cutting-edge AI and 3D modeling technologies. This is a full-time, permanent role offering the chance to contribute to impactful projects in a fast-paced, start-up-like environment centered on scientific exploration and practical innovation. Role Overview: You will be involved in designing, validating, and optimizing deep learning models for 3D reconstruction , with direct application to real-world challenges in agriculture. This is a hands-on research and development position where creativity, technical expertise, and scientific rigor are equally valued. Key Responsibilities: Research & Development : Design, develop, and improve algorithms for 3D modeling and depth estimation using deep learning techniques. Collaboration : Communicate technical findings effectively with team members through documentation, code reviews, and meetings. Scientific Contribution : Support the preparation of academic publications and presentations for conferences in the field. Project Execution : Manage the end-to-end development cycle — from prototyping and testing to deployment and iteration — of AI models and software components. Required Qualifications: Master’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related discipline. Minimum of 1 year experience with deep learning-based dense depth estimation and 3D reconstruction . At least 3 years of hands-on experience with SLAM (Simultaneous Localization and Mapping) and related 3D reconstruction techniques. Proficiency in Python and popular ML/data processing libraries (e.g., PyTorch, TensorFlow/Keras, NumPy, SciPy, OpenCV, Pillow). Strong problem-solving abilities and a solid foundation in mathematics. Ability to write high-quality technical documentation and communicate effectively in a collaborative setting. Preferred Qualifications: Background in geometry, statistics , and the mathematical foundations of machine learning . Understanding of supervised, unsupervised, and self-supervised learning techniques. Familiarity with state-of-the-art methods in 3D deep learning , including topics such as SLAM, SfM (Structure-from-Motion), monocular depth estimation, point clouds, and camera parameter estimation. This is an exciting opportunity for individuals passionate about applying AI to solve complex, real-world problems in sustainability and technology.

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