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extraction, alignment, QC metrics, drift/batch correction) and reporting. Advance annotation strategies using modern approaches such as spectral/structure fingerprinting, molecular networking, in-silico
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methods, which could include but are not limited to: Kriging surrogate, Polynomial Chaos Expansion (PCE), and Physics-Informed Neural Networks (PINNs) Contribute to the strategic direction of research
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research network spanning Prof. McDonald's career accross four continents (USA, Switzerland, Australia, UK) An inclusive and supportive team that values diversity Flexible working hours and partial home
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data or urban mobility patterns Good German language skills (at least B2) Experience with collecting own data (e.g. questionnaires; measurements) Experience with developing networks with stakeholders
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. The opportunity to work with the world-first imaging device tailored to study drift in riverine ecosystems. Access to an extensive network within the field of Ecohydraulics. Scientific independence, visibility and