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., evolutionary algorithms/strategies, mixed-integer search, multi-objective methods). Strong Python and scientific-computing skills (data handling, experiment tracking, testing, version control). Practical
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surfaces. -Structural and biophysical characterization: Exhaustive characterization of the coatings by advanced methods (FTIR, UV-Vis, electron microscopies, TGA, NMR/EPR spectroscopy for structural
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communication skills with both internal and external teams. Ability to work under pressure and manage multiple tasks simultaneously. Proficiency in project management and budget tracking tools. English (high
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areas of nanoscience and nanotechnology. Job Title: Research Assistant - AI Optimisation for Materials Design Research area or group: Theoretical and Computational Nanoscience Group Description of Group
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methods with in situ characterisation techniques such as in situ Raman spectroscopy (including SHINERS) and electrochemical mass spectrometry. This combination will be used to investigate the structure
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) is a training program offering 28 Postdoctoral Fellowships focusing on Planetary Wellbeing and connecting Spanish and Australian research communities. Applicants are invited to propose a research
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characterization techniques. · Knowledge: Deep expertise in electron microscopy, particularly STEM and FIB methods. Proven experience in designing and conducting in-situ TEM experiments. Familiarity with energy
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of energy production in windows prototypes. - Participation to entrepreneurship program. The hired person will be mainly focused on: - lab work to develop the technical part of the project, - Entrepreneurship
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of inorganic or colloidal synthesis methods. Familiarity with microscopy image processing or quantitative analysis tools (e.g., ImageJ, Python-based analysis) will be valued. Motivation to work at the
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and 2D materials, and oxides. Fabrication of functionalized Pb-free MHPs by solution processing methods. Fabrication of complete Pb-free MHPs solar cells and memristors (TFTs). Stability analysis