PComputer Scientists – Deep Learning for 3D Reconstruction in Sustainable Agriculture /ppAn 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. /ppbRole Overview : /b /ppYou 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. /ppbKey Responsibilities : /b /pulliResearch Development : Design, develop, and improve algorithms for 3D modeling and depth estimation using deep learning techniques. /liliCollaboration : Communicate technical findings effectively with team members through documentation, code reviews, and meetings. /liliScientific Contribution : Support the preparation of academic publications and presentations for conferences in the field. /liliProject Execution : Manage the end-to-end development cycle — from prototyping and testing to deployment and iteration — of AI models and software components. /li /ulpbRequired Qualifications : /b /pulliMaster’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related discipline. /liliMinimum of 1 year experience with deep learning-based dense depth estimation and 3D reconstruction. /liliAt least 3 years of hands-on experience with SLAM (Simultaneous Localization and Mapping) and related 3D reconstruction techniques. /liliProficiency in Python and popular ML / data processing libraries (e.g., PyTorch, TensorFlow / Keras, NumPy, SciPy, OpenCV, Pillow). /liliStrong problem-solving abilities and a solid foundation in mathematics. /liliAbility to write high-quality technical documentation and communicate effectively in a collaborative setting. /li /ulpbPreferred Qualifications : /b /pulliBackground in geometry, statistics, and the mathematical foundations of machine learning. /liliUnderstanding of supervised, unsupervised, and self-supervised learning techniques. /liliFamiliarity 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. /li /ulpThis is an exciting opportunity for individuals passionate about applying AI to solve complex, real-world problems in sustainability and technology. /ppJ-18808-Ljbffr /p #J-18808-Ljbffr