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research. You will strengthen the data science and machine learning activities of IAS-9 by developing core AI methods with applications to electron microscopy and materials discovery. You will work in a team
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. State-of-the-art algorithms such as the Gaussian process-based Bayesian optimization have shown high potential tuning radioactive ion beam lines and is currently being the focus of attention in facilities
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experimental molecular biology and data analysis. Doctoral candidates can specialize in genomic and molecular biology techniques, as well as in algorithms, statistics, and artificial intelligence for molecular
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at the interface of machine learning and biostatistics, developing new theory, algorithms, and scalable implementations. By establishing a new class of multi-frame factorization methods, the candidate will
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Inria, the French national research institute for the digital sciences | Pau, Aquitaine | France | about 2 months ago
science as part of the ERC Starting Grant project Incorwave, which aims to develop advanced numerical and mathematical methods for passive seismic imaging. The research will focus on two key-directions: (1
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flexibility for the PhD researcher to develop their own research ideas, and that plans or topics may evolve based on advancements in academic literature or emerging opportunities. Nonetheless, the primary
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The Medicines And Healthcare Products Regulatory Agency; | Canary Wharf, England | United Kingdom | about 2 months ago
services. Responsibilities include leadership of commissioned research; characterising, validating, and integrating new sources of data; monitoring data quality; developing methodologies and algorithms
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28 Feb 2026 Job Information Organisation/Company Tilburg University Research Field Mathematics » Algorithms Mathematics » Applied mathematics Researcher Profile First Stage Researcher (R1
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vulnerabilities like side-channel attacks and unauthorized access, which can compromise system integrity. Developing robust security measures within AI-enabled electronics is essential for applications in defence
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devices Develop hardware-aware machine learning models incorporating electronic and optical device constraints Design and implement hardware-efficient training methodologies for machine learning systems