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to demonstrate prior achievement. University degree in any field with 3–7 years of relevant experience (multiple roles and/or post-PhD), with a strong preference for life sciences or health backgrounds and/or
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for an exceptional and highly motivated PhD candidate for a joint project. We are recruiting a full-time (100%) PhD Student with a strong interest in peptide chemistry, mass spectrometry, and modern drug discovery
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) at ETH Zürich within the Centre for Digital Health Interventions . You will lead the Revelio initiative and co-supervise two PhD students in close collaboration with Prof. Elgar Fleisch (ETH Zürich) and
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relations. The ideal candidate will bring a strong interest in the role of data and technology in shaping environmental governance. We are looking for someone who: Holds a PhD (or will have completed one
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the project will be the assessment of the model results with atmospheric measurements, as well the use of statistical inference methods for hypothesis testing. Finally the improved model will be used to provide
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(PhD, MSc, BSc) and oversee student theses. Develop operational data processing workflows for hyperspectral data and contribute to the design of a software framework for processing multispectral and
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for an outstanding theorist with proven expertise in the broad field of quantum optics and the physics of light-matter interactions. The requirements include a PhD degree in physics or equivalent and an excellent
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spatial and temporal resolution, nuclear magnetic resonance, Mössbauer spectroscopy, or theoretical materials science approaches. These methods should be applied to the study of molecules and solid-state
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collaborate with consortium partners from various scientific disciplines, supervise Bachelor’s, Master’s, and PhD students, contribute to scientific publications, and present your research findings
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applications. Experience with research in these assays is highly desirable. Profile PhD degree in bioinformatics or a related field Proficient in NGS data analysis with excellent scripting skills In-depth