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Field
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and deploying UAV simulation environments using AirSim or its derivatives. Designing and implementing navigation, planning, and obstacle avoidance algorithms using ROS2. Conducting simulation studies
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for ground/space segment threat collection via existing and novel interfaces, including multi-source sensor intelligence collection, fusion and dissemination. 5) Applied forensics for space missions
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training algorithms and AI architecture. Image reconstruction, segmentation, and classification. High performance computing for spatiotemporal data. Major Duties/Responsibilities: Develop foundation AI
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in their computation. We want to understand the fundamental principles that permit us to build privacy-aware AI systems, and develop algorithms for this purpose. The group collaborates with several
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system with integrated sensors. You should hold or be near completion of a PhD/DPhil with relevant experience in the field of robotics, biomedical engineering, information engineering, electrical
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environment project, we will develop automated species and community recognition, particularly focusing on pathogenic soil fungi, with help of deep-learning algorithms fed with microscopic image and Raman
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About Us We are seeking experts in medical image deep learning to join our team and help develop novel computationally efficient segmentation algorithms. We welcome application from individual with
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deep learning to join our team and help develop novel computationally efficient segmentation algorithms. We welcome application from individual with experience in: Deep learning Medical imaging computing
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signals and initiate downstream responses, with a particular emphasis on the mechanistic basis of activation and small molecule modulation. We investigate pathways involving cytosolic DNA sensors
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/functional inequalities Markov processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and