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16.01.2026 – 2:00 PM – Resolution of appeals 16.01.2026 – 4:00 PM – Final results Additional comments We are seeking a PhD student in Machine Learning for EO Image Processing to join our team, who will be
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, load modelling, soil–structure interaction, and relevant degradation and failure mechanisms over extended service periods. Within the scope of the project, a small-scale prototype will be tested in AAU
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fluorescence microscopy, image analysis, and sample preparation for sequencing and multi-omics analyses. The main model organism will be Bacillus subtilis, but other bacteria as well as fungal species including
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congenital human disorders, potentially leading to the development of novel therapeutics for related human diseases. For more information about the Tang Lab can be found through: https://med.virginia.edu/bmg
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learning-based computer vision algorithms and software for object detection, classification, and segmentation. Key Responsibilities Participate in and manage the research project together with the PI, Co-PI
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processes at the molecular, cellular, tissue and systems level of organisation. In so doing we provide a bridge to translational medicine, and interface between physical and life sciences. We are committed
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in the health sciences, including fields such as healthcare informatics, movement and rehabilitation sciences, medical imaging, remote sensing, computer vision, mental health, data fusion
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to outstanding facilities of Genomics, Genetics, Proteomics, Confocal and high-content imaging, Histopathology, Analytical Chemistry, Flow Cytometry, etc. The position is based in the Gliniak lab
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treatment and equal access to the vacancies for all who apply. We ensure an objective and non-biased assessment procedure. Origin, ethnicity, gender, age, employment disability, sexual orientation and other
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computational biophysics Machine learning and data analysis for biological systems Biomedical imaging and signal processing Molecular modeling and simulations AI applications in bioinformatics or health sciences