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Field
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spectroscopy, Stern-Volmer analyses, charge dynamics, electron transfer kinetics for the study of homogeneous systems in solution. A profile with experience of photochemistry studies with soft materials
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or biomolecules into vesicular systems will be considered a strong advantage. Experience with photocatalytic or artificial photosynthesis systems is desirable but not essential. Ability to work independently in
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Institut de Recerca Biomèdica de Lleida, Fundació Dr. Pifarré (IRBLleida) | Spain | about 1 month ago
optical and electron microscopy procedures. ✓ Mastery of cell and molecular biology techniques (immunohistochemistry, western blot, immunoprecipitation, PCR, cloning, etc.). ✓ Experience in surgical and
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documentation and scientific articles, and participating in meetings with partners. Soft skills: Ability to work effectively in international projects and multidisciplinary teams within the field of digital
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conventional electronic-structure and transport techniques become computationally prohibitive. Main Tasks and responsibilities: The researcher will investigate the relationships between atomic structure, degree
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, nanotechnology, chemistry, chemical engineering, printed electronics, micro/nanofabrication, or a related field. Printed electronics techniques, particularly screen printing or inkjet printing. Chemical treatment
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with deep learning to design van der Waals heterostructures with optimised spin-orbit torque (SOT) efficiency for ultra-low-power memory and computing. Its two pillars are AUTOMATA, an automatic material
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biology. Have published research as first author in respected journals. Demonstrate the ability to independently conduct research, supervise students, and maintain scientific rigor. Proficiency in English
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Professional Experience: Demonstrable previous experience in materials science, nanotechnology, chemistry, chemical engineering, printed electronics, micro/nanofabrication, or a related field. Printed
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areas of nanoscience and nanotechnology. Job Title: Junior Postdoc-Electrocatalysis; in situ electron microscopy characterization; deep learning frameworks for TEM image analysis Department: Advanced