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-edge control algorithms for the security and resilience of cyber-physical systems? We welcome you to apply for a PhD position in the SecReSy4You Doctoral Network, a European Union-wide Doctoral Network
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the area of quantum and hybrid classical-quantum networks regarding their design, management, and debugging in distributed architectures. Well-Planned Interdisciplinary Training: To sustainably train PhD
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of Experimental Biology, PAS Type of recruitment: NCN Maestro Requirements: Education: PhD in Neuroscience or Bioinformatics; Professional experience: behavioral and/or molecular neuroscience; or bioinformatics
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convolutional neural networks (CNNs) trained on simulated data, enabling faster and more robust planet detection. 2) Developing a new CDI method using another modulation technique. This PhD will explore how
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-dependent MLCS regulation on lysosomal trafficking, mitochondrial quality control and hypoxia-induced cell death. Please apply for this project using this link: https://www.sheffield.ac.uk/postgraduate/phd
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staff position within a Research Infrastructure? No Offer Description Work group: Institute of Materials and Process Design Area of research: PHD Thesis Part-Time Suitability: The position is suitable
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- 10 Additional Information Eligibility criteria PhD in Chemistry Selection process evaluation of the electronic application, interview https://www.ubbcluj.ro/ro/infoubb/posturi_vacante/files/cercetare
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Informatics) network. This role will focus on the design, implementation, and execution of distributed network studies using electronic health record (EHR) and administrative claims data to generate real-world
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of mechanical cell activity – in this case growth/division and motility. For more information about the network and the project, please visit the central webpage ( https://cafe-bio.org/ ). Your Profile For our
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an interdisciplinary and international environment. Candidates should send their applications by April 30th through https://cv.newton-6g.eu/ Incorporations will begin in May 2026. DC1: Data-driven models for CF networks