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in altermagnets to encode and process information. The project involves close collaboration with experimental and theoretical partners, including large-scale synchrotron facilities. The work will be
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+ EDX · Fully Automated FIB Helios 5UX · FEI SEM Quanta and SEM Magellan Requirements: · Education: PhD in Physics, Materials Science, Nanoscience, Computer Engineering, Data Science. · Knowledge: Deep
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beyond conventional binary "bits" toward multi-level and analog memory systems that enable richer information encoding. A major thrust of the group is the development of in-memory and physical computing
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for energy materials or catalysis, skills on in-situ TEM will be a plus. Experience collaborating in international, multidisciplinary projects is a plus. Hands-on experience working with large-scale research
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, sparsity, and symmetry. Data pipeline: Curate datasets from DFT calculations (and, where relevant, Wannier/TB extractions); implement preprocessing, splits, and rigorous validation. Metrics and validation
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maintenance of the FAIR Knowledge Base, ensuring all experimental and simulation data is searchable and reusable. Professional-grade Python skills with a focus on maintenance. You will be responsible
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the development and assessment of neurotechnology aimed for invasive brain-computer interfaces. In particular, the work will include in vitro assessment of the performance of electrophysiology neural
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of materials and devices following the recently upgraded ISOS protocols and in-situ characterization. Process and analysis of data. Elaboration of periodic reports to keep track of the progress of the project
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of stability protocols for memristor characterizaiton. · Process and analysis of data. · Elaboration of periodic reports to keep track of the project progress. · Preparation of scientific manuscripts and
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. Applicants are invited to propose a research project around the development of AI models for predicting promising catalyst candidates to integrate molecular modelling techniques, experimental data bases and