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the development of artificial systems that each integrate different aspects of machine learning, multimodal sensing, ubiquitous computing and social science. In addition, the successful candidates will have the
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Join us in advancing the frontier of plant sciences and making a tangible impact on agricultural resilience through the power of machine learning! We are seeking a highly motivated PhD candidate
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to computational cardiology. In this project, you will combine advanced physics-based models of the human heart and vasculature with the latest breakthroughs in machine learning to develop scalable and robust
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your chance to make a significant impact in areas such as: Physical layer optimization Signal processing and software-defined radio prototyping Machine learning for wireless sensing What We're Looking
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the content we engage with, the products we purchase, and our social interactions. These systems, driven by machine learning, support a wide range of human decision-making processes across e-commerce, social
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? Then we are excited to get in touch with you. We are looking for a motivated candidate to work on the topics of theoretical machine learning, specifically in the domain of sequential decision-making
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offering competitive compensation. We are also dedicated to providing a supportive and inclusive working environment where you can learn and grow every day. Additionally, you will also receive: A choice of
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of health data or for decision making in health care. You will be developing innovative models, data-driven algorithms, and/or machine learning-based approaches with the goal of profoundly impacting health
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responsible for the maintenance and optimisation of our nanofabrication equipment. You will also instruct users to safely use the equipment and assist them in case of defects or disruptions. As a processing
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of applied cryptography, deep learning methods that are immune to common side-channel defences, machine learning algorithms that can operate on encrypted data in the cloud, detection and mitigation of large