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); Interest/knowledge in cell culture is needed for one of the positions. As we use a combination of methods to gauge the molecular action of drugs, being a strong team player is very important for
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knowledge in NMR is a big plus for the positions. As we use a combination of methods to gauge the molecular action of drugs, being a strong team player is very important for the positions. Our offer A job for
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MMF/Nexus pipeline and the stochastic Bayesian Bisous method. To improve, extend and deepen the analysis to a full dynamical inventory, a major incentive for the project is the application and
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for an excellent and motivated candidate holding a recent Master’s degree in Applied Mathematics, Computer/Data Science, Physics or equivalent. A solid background in PDEs and data science (e.g., model order
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Artificial Intelligence and Structure-Based Drug Discovery (1.0 fte) Background Computational methods have grown to be an integral part of drug discovery over the last three decades. Prior to the ongoing AI
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company’s central hub for advanced data science. With our strong interdisciplinary and enthusiastic teams, we design, build, and apply highly innovative methods using systems biology and artificial
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- and knockoff-based methods that allow for relatively model-free inference. In this project, we aim to combine the strengths of these three frameworks into a novel and coherent whole. The project is
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information combining with parameter estimation methods. Your PhD research will be in the area of applied data-driven scientific computing combining statistics, time-frequency analysis, low-dimensional model
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considered as a manageable proxy. Furthermore, parameter estimation criteria will be considered such as the Fisher information or the Cramér-Rao lower bound, e.g., for estimating the range, Doppler, angle and
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quantitative toxicity assessment in key industrial settings like drug development. In AUTOMATHIC, we aim to develop an integrated framework for automated ODE structure identification, parameter estimation and