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computational tools for bioprocess optimization, combining modeling, simulation, and data-driven methods to improve the efficiency and robustness of microbial and enzymatic production systems. You will design and
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, and high-performance computing for biotechnological applications. The project aims to develop computational tools for bioprocess optimization, combining modeling, simulation, and data-driven methods
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adapt innovative welding processes to be optimally suited for specific applications, we are seeking a new team member at our Ranshofen location. A key focus will be the investigation of innovative welding
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and data documentation Strong understanding of assay development, optimization, and validation processes for use in clinical research applications Background in oncology-related biomarker analysis
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interest in at least one of the following topics is desired: Parallel Computing Cloud Computing Performance Analysis and Optimization Communication Technologies for Supercomputers Workload Management and
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the Tenure Track position, such as Machine Learning, Neural Networks, Optimization, Applied Harmonic Analysis, Inverse Problems, Quantum Information, and other relevant areas. Additionally, the position will
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: Parallel Computing Cloud Computing Performance Analysis and Optimization Communication Technologies for Supercomputers Workload Management and Scheduling Optimization of LLM Training and Inference Our
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important for the Tenure Track position, such as Machine Learning, Neural Networks, Optimization, Applied Harmonic Analysis, Inverse Problems, Quantum Information, and other relevant areas. Additionally
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culture, primary patient material) and molecular, cell biological, and/or biophysical methods (microscopy, qPCR, FACS, etc.) is an advantage. Willingness to learn, optimize, and establish new methods
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productivity through a high degree of prefabrication. A “file to factory” process is to be developed in which static optimization is combined with the creation of production data for robotic systems and/or CNC