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constrains metabolic network architecture despite substantial taxonomic turnover in anaerobic digestion communities, providing a mechanistic explanation for convergent ecosystem functions across similar
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candidate will be expected to work onsite as of their effective start date. This position is for a post-PhD trainee preparing for a research scientist career path. The planned position will provide a
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Position Description Postdoctoral Positions in Theoretical Quantum Matter and Quantum Information Science Swiss Federal Institute of Technology in Lausanne (EPFL) The group of Dr Kruchkov at EPFL
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19 Sep 2026 Job Information Organisation/Company CNRS Department Centre de Recherche en Informatique, Signal et Automatique de Lille Research Field Engineering Computer science Mathematics
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on the theory of deep learning will investigate questions such as the structure and expressivity of emerging neural architectures relevant to space, such as implicit neural fields, continuous normalising
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from multiple departments. The aim is to develop and apply multimodal 3D imaging and analysis frameworks to quantify tissue architecture and protein expression in paraffin embedded tissue samples
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develop and apply multimodal 3D imaging and analysis frameworks to quantify tissue architecture and protein expression in paraffin embedded tissue samples at scale. By integrating AI-drive image analysis
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onsite. Relocation provided for those who qualify. Qualifications We Require: PhD in computer science, mathematics, theoretical neuroscience, physics, or a relevant field conferred within 5 years prior
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tissue architecture. This would allow the same living cells or tissues to be measured and manipulated longitudinally, replacing destructive endpoint workflows with time-resolved experiments and opening a
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computational backbone. You will then transition to PANDORA, an ARPA-E-funded closed-loop AI platform for catalyst discovery targeting CO2 conversion to fuels and chemicals, where the group leads