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We look forward to receiving your application with the following documents as a single PDF: A cover letter indicating which track you are applying for (RL/Optimization, LLM/Knowledge or both) CV
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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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of this project will bring forward the integration of novel methods at the intersection of advanced control, optimization, manufacturing science, robotics, and machine learning. The doctoral student position we
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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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develop and run the weather and climate model ICON. We are seeking a High Performance Computing (HPC) software engineer to further develop and optimize the ICON model (80-100%). Project background In order
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-relevant research challenges such as controlling high precision production machines, optimizing machine tools, or conceiving sustainable manufacturing processes. This position is envisaged to be part of
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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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. 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