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Field
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techniques, like mass spectrometry and genome-wide profiling. Computationally, we analyze our own large data sets and try to integrate results from classical and machine-learning based bioinformatics. Our
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membrane proteins involved in numerous physiological processes. By leveraging machine-learning enhanced virtual screening, the PhD student will be able to perform searches for ligands in chemical libraries
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), and machine learning techniques to identify new players of plant growth during and after an immune response. You will validate the genetic leads, such as transcription factors (TFs), identified in our
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large family of membrane proteins involved in numerous physiological processes. By leveraging machine-learning enhanced virtual screening, the PhD student will be able to perform searches for ligands in
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these CSRS spectra by machine learning algorithms. Your mission is to set up and characterize backscattering CSRS microscopes and evaluate their functionality on cancer tissue. Your tasks will include
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. Novel spectrometer concepts, multi-focus and wide-field illumination approaches will be put in place. Precise diagnoses of cancerous tissues will be derived from these CSRS spectra by machine learning
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. Knowledge of AI and machine learning techniques Experience in the AI application to structural bioinformatics or related areas. Familiarity with the AlphaFold platform and its applications in protein
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another way. If you can say yes to some of the below points it is highly beneficial: Proficiency in programming languages, preferably Python. Knowledge of AI and machine learning techniques Experience in
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another way. If you can say yes to some of the below points it is highly beneficial: Proficiency in programming languages, preferably Python. Knowledge of AI and machine learning techniques Experience in
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friendly solution for mitigating global warming. Due to their high power density, permanent-magnet-based electrical machines are commonly used in electric vehicles. However, these machines have several