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creative and collaborative mindset strong programming skills in Python or Rust strong skills in deep learning systems strong analytical and problem-solving skills fluency in English, both written and spoken
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to countless signals. While traditional approaches have uncovered much of the genetic foundation of response pathways to individual signals, how plants integrate multiple co-occurring signals on the cellular
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transporters based on their structural characteristics. Main activities: -Conduct multiple sequence alignment of plant transporters using phylogeny-aware profiles -Computationally predict and then analyze high
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topics include: Modelling, simulation, and optimisation of integrated energy systems and energy hubs combining multiple vectors, such as electricity, heating, cooling, gas, hydrogen, and transportation
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Applying machine learning-guided directed evolution to improve multiple enzyme properties Upscaling selected biotransformation reactions in collaboration with academic partners Responsibilities and
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digital health technologies Basic programming or data science skills (R, Python) and interest in wearable data analysis are an asset Experience from relevant research projects will be considered as positive
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machine learning and AI research. Strong analytical thinking, problem-solving skills, and the ability to engage with complex data challenges will be greatly valued. Experience with Python or AI frameworks
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such as Matlab or Python is important. This is what we offer you A temporary contract for 38 hours per week for the duration of 4 years (the initial contract will be for a period of 18 months and after
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highly motivated candidate with: Master’s degree in medicine (MD) Strong interest in translational endocrinology and digital health technologies Basic programming or data science skills (R, Python) and
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spectroscopy (UV-Vis, IR, fluorescence). Prior experience with writing code in languages such as Matlab or Python is important. This is what we offer you A temporary contract for 38 hours per week for