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processing methods. Highly motivated and enthusiastic researcher. Strong analytical skills and a keen interest in the interpretation of complex data. Excellent organization skills, time management and ability
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methods. Personal Competences: Highly motivated and enthusiastic researcher. Strong analytical skills and a keen interest in the interpretation of complex data. Excellent organization skills, time
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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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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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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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. 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
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computer-based systems and the preparation of data for inclusion in lab books, presentations and publications. Maintain a hardcopy or electronic lab book · Work in compliance with relevant Health and Safety
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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