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of permanent magnet machines and control systems. Applicants are invited to contact Prof. Z.Q. Zhu at telephone number 2766 6257 or via email at z.q.zhu@polyu.edu.hk for further information. Conditions of
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involves designing, commissioning, and operating a fully automated fermenter system to support advanced bio-manufacturing, including the development of robust protocols for process control, monitoring, and
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Max Planck Institute for Solar System Research, Göttingen | Gottingen, Niedersachsen | Germany | 19 days ago
techniques have enormous potential for the modeling, prediction, and control of nonlinear systems governed by partial differential equations. This project will focus on developing machine learning methods
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project CONSPIRA (Coherent Control of Spin Chains in Graphene Nanostructures, ERC-AdG 101097693). This is an exceptional opening for a motivated and talented physicist to work at the intersection of quantum
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AI and physics‑based simulation for complex mechanical systems. We are now seeking a postdoctoral researcher for a project aiming at physics‑informed autonomous control of machines operating in rough
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Donostia / San Sebastian, Basque Country (Spain), is currently looking for a Pre-doctoral Researcher to work on Spin Coherence and Quantum Control in Graphene Nanostructures. NanoGUNE is a research center
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16 Apr 2026 Job Information Organisation/Company Universite de Montpellier Department Human Resources Research Field Engineering Researcher Profile Recognised Researcher (R2) Positions Postdoc
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background in laboratory automation, control of experimental systems and data‑intensive research. Previous experience in the field of photovoltaics or related optoelectronic devices, particularly organic
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Engineering Design and Optimization Human Factor and Ergonomics AI-based Sensor Fusion Monitoring and Inspection using various sensors Optimization and control to implement sensors. Skills: FEM software (Comsol
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to conduct research in the areas of safety-critical control theory and machine learning. The role will focus on combining new theory or method in nonlinear system control and state-of-the-art machine learning