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below 30 mK and allow the application of magnetic fields to the sample. We characterize the magnetic properties of the quantum systems using standard spectroscopic detection schemes and electron spin
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human patient samples and cutting-edge AI-driven analyses Validate computational findings through functional laboratory experiments Develop and optimize protocols involving omics methods, immune cell
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source for these projects is household survey data, particularly the Demographic and Health Surveys. The group is also working on randomized intervention studies in low- and middle-income country settings
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ability to tackle problems with various techniques, ranging from sample engineering to measurements on fluorescent microscopes (depending on interest, state-of-the-art commercial or custom-built equipment
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functionalities (GUI and web-service) Participate in field work organization, sampling plan establishment and in-situ data acquisition Your Profile PhD in environmental sciences or computer science, with a proven
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publications or writing samples (e.g., Master’s thesis, conference papers) to the following link here quoting “65MIRMIPhD/Postdoc” in the subject line. The review of applications will begin immediately and
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well as the opportunity to design and construct instruments and/or sample environments Establishment of cooperation projects with institutes at Forschungszentrum Jülich working on energy materials Supervision of MSc and
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focus on deep networks for solving inverse problems, learning robust models from few and noisy samples, and DNA data storage. The position is in the area of machine learning, with a focus on deep learning
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small quantum sensors to perform NMR and EPR spectroscopy on nanometer to micrometer small samples, reveal the inner working of Lithium batteries and acquire three-dimensional pictures of single proteins
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August 2025. 1) detailed curriculum vitae 2) copies of degree certificates & transcripts 3) publication record or writing samples from your thesis 4) letters of recommendation (preferably at least two) 5