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to the development of deep learning methods to predict reaction outcomes and optimal reaction conditions for organic reactions. The work will involve model development using Python and/or other programming languages
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development. The successful candidate will contribute to the development of deep learning methods to predict reaction outcomes and optimal reaction conditions for organic reactions. The work will involve model
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, the appointee’s work will cover some of the following areas: Development of an isotope version of the process-based CH4 model and parameter optimization for different wetland types. Coupling the updated CH4 model
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fully automated Prompt calibration which can save tens of person years, millions of CPU hours and speed up the typical CMS analysis cycle times by several years. In addition, it allows better optimization
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necessary for the position. In the postdoctoral researcher's position, the degree requirement (doctoral degree) must be met by the beginning of the employment. The optimal candidates will have acquired a PhD
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experimental (wet-lab) approaches to tackle challenges such as: Prioritizing drug combinations based on single-drug response data Optimizing treatment strategies for synergy, efficacy, and toxicity Deciphering