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-preserving trustworthy distributed machine learning. In this research, the successful candidates will focus on mathematical backgrounds involved in differential privacy to devise novel scalable approaches
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research and experimental work in the fields of sensor networks, biomedical engineering and machine learning with focus on: Utilisation of Inertial Measurement Units (IMUs) in human movement including data
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largely uses traditionally approaches when it comes to laboratory work and synthesis of materials, also here the advent of automation, robotics and machine learning is bringing tremendous change
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. The candidate will collaborate with a multidisciplinary team of researchers and contribute to the advancement of knowledge in this area. Qualifications Master's degree in machine learning Knowledge of deep
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The project will develop new deep learning methods to improve machine vision comprising several sensors in collaboration with industry partners 4AI Systems and 4Tel Pty Ltd. In this project we will
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physical attributes will support and improve the mapping of seagrasses. · Develop machine learning models and object-based image processing algorithms to differentiate and identify seagrass habitat
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applications in engineering areas. additional background or experience in machine learning, data analytics, and other computer science areas would be an advantage experience in power system simulation software
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strong background in artificial intelligence, machine learning, and data analysis. Additionally, experience in healthcare informatics, user experience research, and a commitment to improving mental health
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, computer science, computer vision, or a related domain (a background in medical imaging is advantageous) Proficiency in Python programming or familiarity with deep learning frameworks like PyTorch