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Join our efforts to experimentally build a novel material platform to study quantum phenomena at the atomic scale. If you would like to image, manipulate and study single atoms and molecules
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learning, bioinformatics or advanced statistical methods, to help explore molecular, imaging, clinical and/or epidemiological data. You will apply, adapt and develop machine learning approaches to provide
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which requires code and data sharing and good team work. The duties may also include participation in teaching and other departmental work (however, a maximum of 20% of working hours). Qualifications
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will be responsible for data management and infrastructure, implementation and development of analysis pipelines. You will work on different datasets and help our users with image and downstream analysis
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of the identified structures via stereolithographic, 3D printing and textile techniques like tufting, machine-based embroidery techniques or non-interlaced 3D pre-forming. Development of advanced imaging and
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methods such as NGS, chemical proteomics, and imaging. As the computational lead at CBGE, you will coordinate data-driven projects, spark collaboration across research units, and serve as the key bridge
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on processing and analyzing large sets of medical brain imaging data. We have amassed large quantities of structural MRI (used to measure brain structure), diffusion MRI (used to measure brain connectivity) and
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visualization of complex multimodal results for users who are unused to coding. This will include designing tools for the automatic processing of genomics or other omics datasets, alongside medical or biometric
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or advanced statistical methods, to help explore molecular, imaging, clinical and/or epidemiological data. You will apply, adapt and develop machine learning approaches to provide data analysis support to data
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data types (transcriptomics, proteomics, imaging). Knowledge on AlphaFold for models in structural protein analysis/proteomics AI/ML Applications: Applying machine learning or AI to predict gene function