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PhD students, you will further perform human testing of several prototype devices developed at Delft University of Technology and you will cleverly review and interpret the measurement data
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quality that is not visible in blood or clinical characteristics. By combining the results of AI-driven image analysis of histological samples conducted in this PhD project with biomarker data and outcome
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- Experience in image processing and/or - Familiar with rodent behavioural tests and/or - Experience in histology and/or - Familiar with the theory and preferably practical aspect of MRI. You will be responsible
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representations. In this project, you will substantially improve quantitative magnetic resonance imaging (MRI) image quality using deep learning approaches. Quantitative MRI allows healthcare providers
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one of the following areas: scientific programming and data analysis (e.g., Python, R, C++, MATLAB), computational modeling, imaging and sensor data processing, bioinformatics, systems biology, or
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. These results will provide essential information for anaerobic process design in recycled cardboard industry under water-saving scenarios. This PhD project comprises the following activities: Sorption kinetics
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, the project accelerates trait data acquisition by applying computer vision to herbarium specimens and field photos, as well as large language models to extract complementary information from literature and
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to neurodegenerative disorders. Your PhD project specifically will focus on developing and applying a versatile high-throughput fluorescence imaging platform. In this function you will: optically design a microscope
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) to predict, observe, and manipulate epigenetic processes. The Schneider group is looking for a PhD candidate (f/m/x) to work on the interphase between epigenetics and cellular metabolism. The applicant should
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Required qualifications PhD within forest sciences, remote sensing, data science or related field Competence in data processing and analysis of remotely sensed data Experience in use of remotely sensed data