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in automated extraction, analysis and standardization of multimodal biological, biochemical and medical experimental data Experience with parameter optimization and ODE-based modeling Strong
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Job Description As part of our laboratory's research initiatives, we are conducting advanced research on the computational modeling and optimization of heterogeneous catalysts for various catalytic
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of the mass spectrometry-based proteomic data generated in our chemoproteomics experiments. The postdoctoral associate will be responsible for developing and optimizing custom data analysis and visualization
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twins are leveraged to develop paradigm shifts in quality assurance, quality control, real-time process control, and design optimization for the United States. In this digital environment, you will use
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of Crystallography, RWTH Aachen University. Comprehensive training programs and individual opportunities for personal and professional development Comprehensive company health management Optimal conditions for
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research team. The successful candidate will work on optimizing methods for nanofibers extraction from various types of biomass, focusing on the development of efficient, sustainable, and scalable processes
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associate will lead collaborative efforts in advancing research focusing on the intersection of infrastructure, climate, and human health. Examples of current active projects include: Developing optimization
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-up. In the ZonMW-funded AI for EVAR project, we develop multi-modal models for optimized selection of treatment before, and follow-up after EVAR. You will implement and advance multimodal deep learning
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Your Job: Design and development of a modular high throughput sample environment for chemical hydrogen storage investigations under realistic conditions Design, optimization, and testing of sample
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Programming experience in MATLAB or Python for data analysis Hands-on experience building and optimizing test setups for photonic devices We are looking for someone who is passionate about photonic technologies