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Field
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Science, or a closely related field Prior coursework and working experience in data science, machine learning, statistics, or related areas Proficiency in Python for data analysis and modeling, machine learning
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chemical exchange saturation transfer. By combining multiple modalities and parameters, we aim to identify at risk sites for GBM relapse at the earliest opportunity, before progression becomes apparent
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can also be proposed by the candidate as topics of investigations. The exact focus can be adapted to the candidate’s interests. The project offers flexibility to pursue multiple sub-projects while
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related fire regimes by conducting factorial experiments using multiple climate-change scenarios Requirements: a master’s degree in biophysical, environmental and/or ecological sciences ability to work with
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PhD students (multiple positions) Artificial Intelligence within Public Health Research (all genders) Start date: 01.10.2026 Contract type: 3 years (fixed-term) Location: Wildau Deadline: 30.04.2026
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productivity. Multiple coordinated observing strategies, including research vessels and a large ensemble of autonomous platforms, will collect physical, chemical, and biological datasets across scales
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engineering, or another related field Strong knowledge of Machine Learning theory and methods, and related Deep Learning approaches Excellent knowledge of programming in Python and scientific libraries used
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, extremes, and concept shift Explore equation discovery and dependency-testing ideas to obtain deterministic, interpretable representations of plant carbon allocation and plant water status Integrate multiple
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concentrates on global design of the turbomachinery stages for decarbonization. PhD Objectives The overarching objective of the PhD thesis research project is to combine numerical tools with multiple levels
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will use and develop Python scripts for analysing results and may participate in the development of codes such as the observation simulator and the improvement of the controller. The proposed thesis will