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of polymer characterization techniques (e.g., FTIR, NMR, SEC, TGA, DSC, SEM, XRD, BET, UV–Vis, ICP-OES/MS, or related analytical methods). Experience with ion-exchange polymeric resin synthesis, green
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methods and tools is highly required. Good experience with AI methods is highly appreciated. Good communication skills, both verbal and written, are important. Fluence in French and English is required
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processing. . A strong programming background and use of HPC are required. A very good knowledge of statistical methods and tools is highly required. Good experience with AI methods is highly appreciated. Good
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methods is a plus Programming experience in MATLAB and/or Python Familiarity with process simulation software such as Aspen Plus or Aspen HYSYS Application and Selection: The application folder must contain
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experimental work in chemical or process engineering (desirable) Knowledge of process optimization, parameter estimation, or control methods is a plus Programming experience in MATLAB and/or Python Familiarity
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databases based on experimental and computational data. Establish predictive models based on artificial intelligence methods. Utilize the developed models to design and optimize the properties of materials
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of different P-based materials via the sol-gel and solvothermal methods with control over morphology, particle size, and composition. Material characterization using XRD, SEM, EDS, ICP, BET, TGA, FTIR, RAMAN
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chemistry of materials, materials science, electrochemistry, materials synthesis and battery research. Key responsibilities: Synthesis of different P-based materials via the sol-gel and solvothermal methods
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Requirements: The successful candidate is expected to: Build and evaluate chemical databases based on experimental and computational data. Establish predictive models based on artificial intelligence methods