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The candidate will optimize an instrumentation and a microfluidic card for encapsulating human cells in monodisperse microbeads of extracellular matrix. Within a few days, cells encapsulated in microbeads form organoids or tumoroids, which are miniature 3D cellular models of biological tissues...
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(Principal Investigator) and Dr Robin McKenna (Co-Investigator) who are both based at The University of Liverpool, UK, and a postdoctoral researcher also based in Liverpool. The main tasks will be to: Survey
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Design Space Exploration for Next-Generation Computing Systems. This position in fixed-term contact is based at Nano-Innov (CEA Paris-Saclay), Essonne (91). This position is available as soon as possible
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both spoken and written is required The candidat must have a Master (M2) of data science, computer science, applied mathematics The position is available starting from October. Salary according
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at the interface of machine learning and computational neuroscience. The candidate will be part of the COATI joint team between INRIA d’Université Côte d’Azur and the I3S Laboratory. Project The candidate should
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, Technology and Medicine of the University of Luxembourg is opening for its Department of Engineering (DoE) a new Associate Professor or Assistant Professor (tenure track) position in Computational Fluid
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Term Contract 24 Month Work Hours: Full Time 40.0 Hours per Week Planned start date: November 1st 2025 Location: Campus Belval Internal Title: Postdoctoral researcher Job Reference: UOL07307 The yearly
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Interstellar Chiral Molecules – from amorphous interstellar ices to evolved planetary systems Objective: We are seeking a motivated and skilled doctoral student to join our team at the Institut de Chimie de Nice as part of the ERC Consolidator Grant ICE-EEVOLVE . This ambitious project aims to...
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Master's degree in Epidemiology, Public Health or a related field. Applicants should be enrolled in a Master program and the internship should be a mandatory part of the diploma; Experience in working
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, copyrighted, or biased. By studying brain data recordings and building computational models that mimic real populations of neurons, the project aims to uncover active unlearning: how the brain learns