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to join an interdisciplinary project at the interface of single-cell genomics, data integration, and developmental biology. The project focuses on the integration and analysis of multi-modal single-cell
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prototypes for portable and reconfigurable automation, as well as explore how these solutions can be integrated into industrial environments with requirements for flexibility, quality, and resource efficiency
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Researcher position. The selected candidate will work on research and development for testing, analysis, and integration of AI and machine learning (ML) algorithms in new simulation and training architectures
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ferroelectric memory, photonic integrated circuits and next-generation telecommunications. You'll work at the exciting intersection of experimental materials science and materials informatics, collaborating in
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, efficiency, and functionality. You will contribute to one of four complementary research directions: ALD for photonic integration: Development of functional dielectric coatings for III–V nanophotonic
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engagement; inclusion and diversity; and respect and integrity. As such, we see the importance of recruiting talent aligned to these values and are looking for a Postdoctoral Research Associate in
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or mentor students and junior researchers commitment to research integrity, laboratory safety and inclusive research practices Pre-employment checks and declarations Your employment is conditional upon
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fully understand the methods and the models (MILP, SAT or CP), develop models dedicated to other block ciphers or integrate the new models into a dedicated tool such as TAGADA, CLAASP or another tool
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N and C transfer using bacteria as partners in plant nutrient acquisition, and symbiosis under variable nutrient conditions. The project will integrate controlled plant–microbe experiments with
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Job Description Here's a Glimpse of the Job The Postdoctoral Research Associate will be involved in developing deep learning architecture for multi-object data integration, federated learning approaches