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experimental parameters (time, temperature). To optimize these parameters, active learning techniques based on Bayesian optimization will be applied. In situ or ex situ characterizations (FTIR, ¹¹B/¹H NMR, HP
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RESEARCHER PROFILE: Postdoc/R2: PhD holders RESEARCH FIELD(S)1: Physics MAIN SUB RESEARCH FIELD OR DISCIPLINES1: Engineering JOB /OFFER DESCRIPTION This post-doctoral position will be realized within
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and mRNA translation. The successful candidate will establish live imaging tools to analyse translation dynamics in regenerating axons, using an ex vivo culture model previously optimized (Schaeffer et
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” focusing on the effect of a fluctuating environment on the collective dynamics of self-propelled agents, a numerical part on “reinforcement learning” focusing on optimizing communication between agents in a
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, Uncertainty, Data SCOP: Reliability, Communication, Optimization SyRI: Robotic Systems in Interaction The recruited postdoctoral researcher will join the CID team, whose research focuses on Artificial
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under periodic conditions. SOC and excited-state geometry optimizations will help identify ISC/RISC probabilities and the specific components involved. These insights will clarify how each molecular
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term [2]. In this context, the aim is to develop NIR-selective photosensitizers, which is precisely the subject of the present PhD offer. The TRANSCEND project, funded by the Pays de la Loire region
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to efficiently identify materials with optimal mechanical properties and controlled degradability. The primary task is to develop techniques for synthesizing degradable polymers and copolymers using ring-opening
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research contractors. Through the design and characterization of new materials, the laboratory's approach leads to the optimization of a wide range of properties for targeted applications. The position is in
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15 Sep 2025 Job Information Organisation/Company INSERM U1183 Department U1183 Research Field Biological sciences » Biological engineering Researcher Profile Recognised Researcher (R2) Positions PhD