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the possibility of an extension. TASKS: Mathematical modeling and development of inverse methods (e.g. Bayesian inversion, optimization based methods, sparsity promoting methods based on L1-norm minimization and
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(written and spoken English) and presentation skills. • Ability to work in a team, with effective interpersonal communication skills. • Willingness to assist with the supervision of BSc, MSc and PhD work Our
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on the nanoscale (previous works e.g.: https://www.nature.com/articles/s41563-019-0555-5). You will also supervise one PhD student who will work on a complementary topic guaranteeing quick output and an ideal
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to an international competitive PhD degree and internationally peer-reviewed publications. This includes participation in selected nationally and internationally funded projects of the Chair Group, such as the EU
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presentation skills. • Ability to work in a team, with effective interpersonal communication skills. • Willingness to assist with the supervision of BSc, MSc and PhD work Our offer We offer an interesting and
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. Your qualifications An excellent PhD degree either in Computer Science, Physics, Mathematics or related fields, ideally with a background in quantum theory, quantum computing or quantum machine learning
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, methods, and algorithms into existing high-performance frameworks, the fast prototyping of new ideas in individual code, an interest in the entire simulation pipeline: starting from simple algorithms
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to 5 and more years. Requirements: • You have a PhD degree (or postgraduate degree MSc) in a computational discipline, preferably with significant experience in Bioinformatics or Computational Biology
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preliminary work! • You will characterize metalloid transport proteins. • You will be involved in the training of students on the Bachelor and Master level. YOUR QUALIFICATIONS AND SKILLS • You have a PhD or
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sensitivities, i) hyperpolarization methods must be applied, and the NV-NMR detection must be improved. In the project, these technological developments will be combined with applications in single-cell biology