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has a well established reputation for wide-ranging research with an emphasis on long-term processes, and with economic theory and quantitative methods as important methodological tools. Strong research
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requirements for doctoral studies, you must: hold a Master’s (second-cycle) degree in engineering physics, electrical engineering, machine learning, data science, computer vision, computer science, applied
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and visualization of metabolomics data, support the integration of software tools for data (pre-)processing, biomarker discovery, and predictive modelling. Furthermore, serve as the metabolomics subject
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/ his main activity (work, studies etc.) in Germany for more than 12 months in the past 3 years. Selection process The application should be written in English and be attached as PDF-files, as below
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polymers and on the development of spinning processes for manufacturing conducting polymer fibers used in wearable electronics. A summary of the research field can be found in a recent review . Project
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. They involve high-stakes decisions with important trade-offs and uncertainties. They are also challenged by the data sampling process which gives rise to distribution shifts when comparing past and future data
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novel machine learning method development. However, you will be part of a larger cross-disciplinary research initiative involving both computer and material scientists, providing excellent opportunities
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qualifications Marine biogeochemical processes Hydrodynamic processes related to ships, turbulence, or mixing Oceanographic modelling Data analysis and programming (e.g., MATLAB, Python, or R) Interdisciplinary
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to ensure optimal tissue concentrations during surgery. The PhD student will utilise national and international arthroplasty registry data, adapt in vitro diagnostic tools such as the Minimum Biofilm
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Description: Broadleafification, i.e. the process of increasing the share of broadleaf tree species within conifer-dominated forests, is a promising strategy for biodiversity conservation in managed (hemi