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Field
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describing the electron optics of the projection column and optimize its performance through large-scale simulations. You will use commercial electron-optical simulation software but also develop custom Python
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electronic health record (EHR) data; apply ML methods (especially deep learning methods) to solve critical medical problems. Implement methods into software that meets research needs, manage and update source
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computing, hardware-software co-design, FPGA development, or hardware-accelerated computing will be considered a strong advantage. Familiarity with efficient-deployment toolflows such as TinyML or FINN is a
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is helping to make completely sustainable and future-proof. At the same time, we are developing the chips and sensors of the future, whilst also setting the foundations for the software technologies
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future-proof. At the same time, we are developing the chips and sensors of the future, whilst also setting the foundations for the software technologies to run on this new generation of equipment – which
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and passive RF localisation using software-defined radio. A central theme of the project is co-design across sensing, AI reconstruction, and embedded deployment. You will explore how multimodal models
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learn new things - A strong programmer who’s comfortable with Python - An open-minded thinker and precise communicator who enjoys collaborating with colleagues from a wide range of backgrounds and areas
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or related topics will be considered an advantage, as will familiarity with common tools for hydrological and hydrogeological modelling, but it is not a requirement that you already master specific software
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robotics software frameworks such as ROS/ROS 2. You will be expected to work both independently and collaboratively in an international research environment, with excellent written and spoken English skills
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, environmental research, and open-source software development. You'll contribute to tools and knowledge that directly inform how we monitor and respond to some of the planet's most pressing environmental