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. A successful candidate should have very good knowledge in quantitative methodology and related analysis tools, in particular very good knowledge in analysis with registry or survey data from various
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Physicochemical and spectroscopic characterization of substrate performance, including sensitivity, reproducibility, stability, and matrix effects Quantitative analysis of spectroscopic data using multivariate
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conferences and journals, with experience in one or more of the following areas: mathematical analysis of AI models in terms of correctness of outcomes, neuro-symbolic reasoning in cybersecurity, efficient
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platforms, security analysis, adversarial AI attacks and defences, intrusion detection, load management in mobile edge networks, or denial-of-service detection are considered as a merit. Earlier experience in
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of performance and stability in Na- and Zn-based batteries. The work also involves data analysis, method development, and systematic documentation of research results. Furthermore, the postdoctoral researcher is
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. Documented research experience and knowledge of behavioural biology are required. You should also have solid experience working with large datasets, as well as documented skills in statistical analysis and
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of novel 2D materials (e.g., thin-film deposition by PVD and CVD). Proven programming skills (e.g., Python) for instrument control and data analysis. You are a highly motivated and independent researcher