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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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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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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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- 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
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science. A wide range of quantum theoretical methods shall be employed. A solid background in quantum mechanics and programming skills are prerequisite for this position, as is the readiness to learn and to
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scientific challenge. The planned PhD project will therefore investigate the interaction of food-borne toxicants with realistic co-exposure using New Approach Methods (NAMs). The focus will be