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Field
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the analysis of multimodal spatial omics data across multiple projects, collaborating closely with experimental biologists. Main tasks and responsibilities: Develop and implement robust computational pipelines
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research outputs. The candidate will need to demonstrate agility in managing and leading multiple projects and work independently in this ever-changing and fast-paced sector. The position is funded by CAR, a
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, Prof Anton van den Hengel and his research team to publish research outputs. The candidate will need to demonstrate agility in managing and leading multiple projects and work independently in this ever
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Engineering, Aerospace Engineering, or a related field. Degree must be conferred upon hire. Preferred Qualifications Applied expertise in optimal control, heuristic optimization, graph search algorithms, and
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algorithms, and machine learning to solve complex aerospace engineering challenges. Developed and implemented AI-driven solutions for autonomous lunar and asteroid landings, as well as cislunar operations
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technology and develop human resources. The AI Computing Team explores the design and realization method of advanced machine learning systems by working across multiple layers, including circuits, devices
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wide range of resources and is mostly not publicly available. While sharing proprietary data to train machine learning models is not an option, training models on multiple distributed data sources
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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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world networks have a multidimensional nature such as networks that contain multiple connections. For instance, transport networks in a country when considering different means of transportation
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large quantities of data to gain a greater understanding of our systems and develop data analytics and artificial intelligence algorithms. You will be actively engaged in the research and development