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the Phytophotonics department, you will work as part of an interdisciplinary team at the interface between plant sciences and optical technologies. The focus is on various spectroscopic and imaging methods
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learning and data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms
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breakage models, e.g. with stochastic tessellations Development and implementation of estimation methods for the model parameters, e.g. with machine learning or statistical methods Lab work and collection
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and exploration of novel P-compounds. Characterization of the obtained products and intermediates via spectroscopic methods such as NMR, UV-vis, IR/Raman, mass spectrometry and X-ray structure
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consisting of PAT and mechanistic / data driven modelling allowing process control. Steps to be taken will be: Developing a process applicable PAT method (single / multisensoric) for AAV / LNP / VLP detection
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methods/simulations, state-of-the-art computational techniques (e.g. data-driven methods and/or FEM) and/or theoretical material modeling will be given preference We offer: chance to collaborate with
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of their studies, students are exposed to a wide range of scientific questions and methods covering molecular medicine, neuroscience, and clinical psychiatry. Methods range from molecular genetics over
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- and Q-band EPR spectrometer. The candidate will be responsible for designing, building, and optimizing instrumentation and methods to investigate complex catalytic systems — including both synthetic and
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. The successful candidate will use advanced spectroscopic methods to study the structure and reactivity of nitrogenase enzymes and biomimetic complexes, contributing to a broader effort to understand
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: Syntheses of new phosphorus-rich heterocycles, their follow-up chemistry and application as opto-electronic material. Characterization of the obtained products and intermediates via spectroscopic methods