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datasets and sophisticated modelling techniques to evaluate and optimize energy systems. We have developed in-house tools and utilize open-source datasets to support our research activities in various
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approaches toward sustainable dairy farming, leveraging advanced statistical modeling, machine learning, and AI to uncover biological insights and optimize production efficiency, animal health and
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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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an interest in bridging rigorous theoretical insights with challenging real-world tasks. They will also explore reinforcement learning strategies to optimize decision-making policies in complex
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, precision livestock farming, and multi-omics approaches toward sustainable dairy farming, leveraging advanced statistical modeling, machine learning, and AI to uncover biological insights and optimize
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programming, modelling, and data analysis skills. Experience with formulating and solving mathematical optimization problems is an asset. Proficiency in English is required; good comprehension and oral skills
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analysis. Experience in formulating and solving mathematical optimization problems is an asset. Proficiency in English is required; good comprehension and oral communication skills in German are desirable
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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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hands-on learning experiences or with computational elements relevant to Artificial Intelligence or Optimization, in addition to running your research group. Since this is a leadership position, your
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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