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), the sorption of PFAS and heavy metals onto natural nanoparticles will be investigated in situ using a dedicated field exposure method developed by our team, complemented by laboratory experiments and machine
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engineering (e.g., software architecture, development processes, quality assurance). Very good programming skills (at least in Python and C++); ideally strong hands-on experience with ROS2. Experience in AI
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Experience in experimental work and instrumental analytics Knowledge of elemental and colloid analytics as well as microscopy is an advantage Readiness to handle open radioactive materials in a radiation
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than the start of the contract) demonstrated expertise in molecular and cell biology techniques and ideally prior in-depth experience with in particular high-resolutionimaging, but also cell culture and
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with experimental, numerical in collaboration with other RTG members (fellow students and supervising professors) implementation of the planned research program, evaluation and interpretation
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or population genetics/genomics and have a strong interest in studying genetic biodiversity. Previous experience with molecular lab work is a must; additional skills in bioinformatics and/or statistics
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training in the technical tasks of the individual dissertation topics through study of the literature and in making the objectives more precise; working on the individual PhD study project with experimental
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assimilation towards experimental measurements under consideration of uncertainties utilization of Explainable AI techniques to enable novel scientific discoveries implementation of your machine learning