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learning-based computer vision algorithms and software for object detection, classification, and segmentation. Key Responsibilities Participate in and manage the research project together with the PI, Co-PI
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will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep learning-based computer vision algorithms and software for object detection, classification, and
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will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep learning-based computer vision algorithms and software for object detection, classification, and
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degree will definitely be advantageous. Knowledge of machine learning, pytorch, huggingface etc... Knowledge of image processing is required. Ability to effectively and efficiently utilise industry
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/ Electronics Engineering, Computer Engineering, Computer Science, Robotics, or a closely related discipline, with foundational knowledge in signal processing and machine learning. Working knowledge of computer
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of wireless communications, edge computing, and machine learning, and who is eager to translate theoretical insights into practical systems. Key Responsibilities Derive and analyse closed-form mathematical
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Science, or a related technical field Master's or PhD degree in Machine Learning, Computer Vision, or related areas will be advantageous Preferred Qualifications: Experience with biological/ecological
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As a University of Applied Learning, SIT works closely with industry in our research pursuits. Future ship and system design (FSSD) program develop strategic and innovative design capabilities
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++. Demonstrable experience with machine learning frameworks (e.g., PyTorch, TensorFlow). Hands-on experience with game AI agents and/or GUI agents such as Mineflayer, Unity ML-Agents, or similar. Solid expertise in
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, microbial cultures, and cleaning validation samples. Develop data analysis pipelines for Raman spectral classification, potentially integrating machine learning methods. Research & Project Responsibilities