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with solid-state fermentation (SSF) using filamentous fungi to optimize nutrient profiles in food. The goal is to develop predictive models in fermentation processes to achieve enhanced nutritional
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the bacterial import process, optimizing the system for high performance, and then applying it to problems around therapeutic peptides and proteins. The focus of the work is experimental and will include a broad
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would build upon the laboratory's past and ongoing work within the context of AI-guided Design, Inverse Design, and Optimization across different application domains. In particular, we are developing
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. Additional familiarity with building your own embedded sensing sensing setup is a strong plus (e.g., for EMG/ECG/EOG or other differential or regular sensors). An optimal background for the project would be
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the Multiphase Fluid Dyamics group (Prof. Supponen) has a focus on modelling and high-speed imaging to optimize bubble generation and control, and the resulting particle dynamics and interaction with cells using
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. The optimal exploitation of digital tools in system development processes facilitates an effective and efficient process. To effectively capitalise on the existing knowledge base, digital tools, e.g., large
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experience in developing software for scientific applications, data analysis, or real-time systems is desirable. Experience with parallel computing and optimization techniques for handling large datasets
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100%, Zurich, fixed-term We are seeking a skilled Machine Learning Engineer to join our dynamic team. The ideal candidate will be involved in the development, optimization, and maintenance of our
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mechanisms underlying bacterial infections and the emergence of antimicrobial resistance, and (2) evaluate novel treatment strategies. A key objective is to optimize the platform for translational applications
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/jiec.13205 Komkova A., Habert G. 2023. Optimal supply chain networks for waste materials used in alkali activated concrete fostering circular economy. Resources, Conservation & Recycling. DOI:10.1016