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reports, and summaries of results, as well as contributing to scientific publications and project-related deliverables. Role in the project: Position 1 - Design and conducting experiments: synthesis and
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experiments, data analysis. The successful candidate will be responsible for designing and conducting experiments, including the synthesis, purification, and characterization of peptides and peptide-based
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Łukasiewicz Research Network - Institute of Microelectronics and Photonics | Poland | about 17 hours ago
, physics, electronics, materials engineering, or a related field will be preferred. Experience in conducting research and development work related to the design, modelling or characterisation of photonic
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involve conducting computer simulations and computational studies as part of the research project titled "Design, characterization, and description of the mechanisms of action of heterostructural
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, Flash) Knowledge of basic spectroscopic methods used to identify organic compounds (NMR, FTIR, CD, UV-vis, fluorescence) Ability to design and perform syntheses of organic compounds Experience in working
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classes. Additional requirements: submission of short plan for the attainment of an academic degree, authorship or co-authorship of scientific publications and other forms of presenting research findings
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Academy of Sciences on 5 December 2024 (in Polish [https://pan.pl/app/uploads/2025/02/KodeksEtykiPracownika.pdf ]). CAMK PAN subscribes to gender principles in the Strategic Plan 2021+, where it has
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of single vortex in superconducting nanostructures including the design and fabrication of samples using electron-beam nanolithography and performing the corresponding simulations using the Ginzburg–Landau
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COMPETITION FOR THE POSITION OF ASSISTANT LECTURER (F/M) IN THE TEACHING STAFF GROUP (Ref. No. 3979)
related to the research conducted in the Department of Functional Materials Engineering * basic experience in research on functional materials properties * fluent communication in English (min. B2) * very
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, classical training with quantum sampling, and analysis of expressivity, trainability and potential quantum advantage. Machine learning for quantum experiments: Methods for experimental design, adaptive