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available on site for the development of suitable radiotracers. One focus of the work is on the use and evaluation of large tomographic data sets to derive parameter data for reactive transport modeling
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Master’s degree in Data Science, Artificial Intelligence, Computational Linguistics, Computer Science. Has excellent academic writing and oral skills in English. Has experience with large language models
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-developing the principles (e.g. ethics) and methods for anonymising, processing and analysing sensitive data collected by a national charity’s 24/7 helpline for people experiencing or witnessing elder abuse
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create a working framework that includes both experimental and modelling prototypes, including AI/ML tools to assist with the large number of variables involved. This project is seeking candidates with a
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engineering, clinical research, and AI-driven health monitoring. This project will explore large-scale maternal datasets—combining clinical cardiovascular assessments with wearable sensor data—to detect early
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supervisors and fellow researchers, you will contribute to the development of solvers for combinatorial optimization problems and apply them to real-world data from industrial partners. As part of your PhD, you
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of testicular tissue Validate gene expression at the protein level via IHC and Western blotting Analyze large-scale transcriptomic data (R, Python) Test allele-specific regulatory activity using luciferase
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its processing capabilities but also its adaptability, leveraging early developmental data and ecological validity. Infant data will be acquired in collaboration with Dr. Tessa Dekker (University
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biological data, development of deep learning and large language models for biological discovery or graph-based methods for molecular and cellular networks. The technological foundation further consists
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considers the transport of suspended matter (tracers); calibrating and validating the model against long-term data on hydraulic conductivity, water temperature, and dissolved oxygen from several rivers